Multi-scale consistent self-training network for semi-supervised orbital tumor segmentation.

PURPOSE: Segmentation of orbital tumors in CT images is of great significance for orbital tumor diagnosis, which is one of the most prevalent diseases of the eye. However, the large variety of tumor sizes and shapes makes the segmentation task very challenging, especially when the available annotation data is limited. METHODS: To this end, in this paper, we propose a multi-scale consistent self-training network (MSCINet) for semi-supervised orbital tumor segmentation. Specifically, we exploit the semantic-invariance features by enforcing the consistency between the predictions of different scales of the same image to make the model more robust to size variation. Moreover, we incorporate a new self-training strategy, which adopts iterative training with an uncertainty filtering mechanism to filter the pseudo-labels generated by the model, to eliminate the accumulation of pseudo-label error predictions and increase the generalization of the model. RESULTS: For evaluation, we have built two datasets, the orbital tumor binary segmentation dataset (Orbtum-B) and the orbital multi-organ segmentation dataset (Orbtum-M). Experimental results on these two datasets show that our proposed method can both achieve state-of-the-art performance. In our datasets, there are a total of 55 patients containing 602 2D images. CONCLUSION: In this paper, we develop a new semi-supervised segmentation method for orbital tumors, which is designed for the characteristics of orbital tumors and exhibits excellent performance compared to previous semi-supervised algorithms.

Development of a Clinicopathological-Radiomics Model for Predicting Progression and Recurrence in Meningioma Patients.

RATIONALE AND OBJECTIVES: Tumor progression and recurrence（P/R）after surgical resection are common in meningioma patients and can indicate poor prognosis. This study aimed to investigate the values of clinicopathological information and preoperative magnetic resonance imaging (MRI) radiomics in predicting P/R and progression-free survival (PFS) in meningioma patients. METHODS AND MATERIALS: A total of 169 patients with pathologically confirmed meningioma were included in this study, 54 of whom experienced P/R. Clinicopathological information, including age, gender, Simpson grading, World Health Organization (WHO) grading, Ki-67 index, and radiotherapy history, as well as preoperative traditional radiographic findings and radiomics features for each MRI modality (T1-weighted, T2-weighted, and enhanced T1-weighted images) were initially extracted. After feature selection, the optimal performance was estimated among the models established using different feature sets. Finally, Cox survival analysis was further used to predict PFS. RESULTS: Ki-67 index, Simpson grading, WHO grading, and radiotherapy history were found to be independent predictors for P/R in the multivariate regression analysis. This clinicopathological model had an area under the curve (AUC) of 0.865 and 0.817 in the training and testing sets, respectively. The performance of the combined radiomics model reached 0.85 and 0.84, respectively. A clinicopathological-radiomics model was then established, which significantly improved the prediction of meningioma P/R (AUC = 0.93 and 0.88, respectively). Finally, the risk ratio was estimated for each selected feature, and the C-index of 0.749 was obtained. CONCLUSION: Radiomics signatures of preoperative MRI have the ability to predict meningioma at the risk of P/R. By integrating clinicopathological information, the best performance was achieved.

Free water and iron content in the substantia nigra at different stages of Parkinson's disease.

PURPOSE: Abnormalities in free water (FW) and susceptibility values exist in the substantia nigra (SN) of patients with Parkinson's disease (PD), but their role in characterizing the disease processes remains uncertain. This study investigated these values at various SN locations and stages of PD, and their relationship with clinical symptoms. METHOD: FW and quantitative susceptibility mapping (QSM) values were evaluated in the anterior and posterior SN, along with swallow-tail-sign (STS) ratings, in patients with PD (early-stage: n = 39; middle-to-advanced-stage: n = 97) and healthy controls (n = 82). The correlation between these indices and motor and non-motor symptoms, and their capability to distinguish PD from healthy controls, were also examined. RESULTS: Increased FW in the anterior and posterior SN and increased QSM values in the posterior SN were observed in both early-stage and middle-to-advanced-stage PD patients (p < 0.05). However, there was no significant difference in FW, QSM values, or STS ratings among patients at different stages. FW and QSM values correlated with motor symptoms in middle-to-advanced-stage patients (p < 0.05), while STS ratings were associated with non-motor symptoms (p < 0.05). Additionally, combining FW and QSM values in the posterior SN with STS ratings in logistic regression showed better performance in distinguishing PD (area under curve = 0.931) compared to using STS ratings alone (area under curve = 0.880). CONCLUSIONS: Findings suggest elevated FW and iron content in PD at different stages, with dissociation in SN location between the two indices. Elevated signals are related to the motor symptom severity in middle-to-advanced-stage patients, and may have the potential for PD diagnosis and symptom assessment.

Direct localization and delineation of human pedunculopontine nucleus based on a self-supervised magnetic resonance image super-resolution method.

The pedunculopontine nucleus (PPN) is a small brainstem structure and has attracted attention as a potentially effective deep brain stimulation (DBS) target for the treatment of Parkinson's disease (PD). However, the in vivo location of PPN remains poorly described and barely visible on conventional structural magnetic resonance (MR) images due to a lack of high spatial resolution and tissue contrast. This study aims to delineate the PPN on a high-resolution (HR) atlas and investigate the visibility of the PPN in individual quantitative susceptibility mapping (QSM) images. We combine a recently constructed Montreal Neurological Institute (MNI) space unbiased QSM atlas (MuSus-100), with an implicit representation-based self-supervised image super-resolution (SR) technique to achieve an atlas with improved spatial resolution. Then guided by a myelin staining histology human brain atlas, we localize and delineate PPN on the atlas with improved resolution. Furthermore, we examine the feasibility of directly identifying the approximate PPN location on the 3.0-T individual QSM MR images. The proposed SR network produces atlas images with four times the higher spatial resolution (from 1 to 0.25 mm isotropic) without a training dataset. The SR process also reduces artifacts and keeps superb image contrast for further delineating small deep brain nuclei, such as PPN. Using the myelin staining histological atlas as guidance, we first identify and annotate the location of PPN on the T1-weighted (T1w)-QSM hybrid MR atlas with improved resolution in the MNI space. Then, we relocate and validate that the optimal targeting site for PPN-DBS is at the middle-to-caudal part of PPN on our atlas. Furthermore, we confirm that the PPN region can be identified in a set of individual QSM images of 10 patients with PD and 10 healthy young adults. The contrast ratios of the PPN to its adjacent structure, namely the medial lemniscus, on images of different modalities indicate that QSM substantially improves the visibility of the PPN both in the atlas and individual images. Our findings indicate that the proposed SR network is an efficient tool for small-size brain nucleus identification. HR QSM is promising for improving the visibility of the PPN. The PPN can be directly identified on the individual QSM images acquired at the 3.0-T MR scanners, facilitating a direct targeting of PPN for DBS surgery.

Increased iron deposition in nucleus accumbens associated with disease progression and chronicity in migraine.

BACKGROUND: Migraine is one of the world's most prevalent and disabling diseases. Despite huge advances in neuroimaging research, more valuable neuroimaging markers are still urgently needed to provide important insights into the brain mechanisms that underlie migraine symptoms. We therefore aim to investigate the regional iron deposition in subcortical nuclei of migraineurs as compared to controls and its association with migraine-related pathophysiological assessments. METHODS: A total of 200 migraineurs (56 chronic migraine [CM], 144 episodic migraine [EM]) and 41 matched controls were recruited. All subjects underwent MRI and clinical variables including frequency/duration of migraine, intensity of migraine, 6-item Headache Impact Test (HIT-6), Migraine Disability Assessment (MIDAS), and Pittsburgh Sleep Quality Index (PSQI) were recorded. Quantitative susceptibility mapping was employed to quantify the regional iron content in subcortical regions. Associations between clinical variables and regional iron deposition were studied as well. RESULTS: Increased iron deposition in the putamen, caudate, and nucleus accumbens (NAC) was observed in migraineurs more than controls. Meanwhile, patients with CM had a significantly higher volume of iron deposits compared to EM in multiple subcortical nuclei, especially in NAC. Volume of iron in NAC can be used to distinguish patients with CM from EM with a sensitivity of 85.45% and specificity of 71.53%. As the most valuable neuroimaging markers in all of the subcortical nuclei, higher iron deposition in NAC was significantly associated with disease progression, and higher HIT-6, MIDAS, and PSQI. CONCLUSIONS: These findings provide evidence that iron deposition in NAC may be a biomarker for migraine chronicity and migraine-related dysfunctions, thus may help to understand the underlying vascular and neural mechanisms of migraine. TRIAL REGISTRATION: ClinicalTrials.gov, number NCT04939922.

Genetic impacts on nigral iron deposition in Parkinson's disease: A preliminary quantitative susceptibility mapping study.

BACKGROUND: Dysfunction of iron metabolism, especially in substantia nigra (SN), is widely acknowledged in Parkinson's disease (PD), but the genetic influence on iron deposition remains largely unknown. Thus, in this study, we aimed to investigate potential genetic impacts on iron deposition in PD. METHODS: Seventy-four subjects, including 38 patients with PD and 36 age-matched normal controls, participated in this study. Imaging genetic association analysis was used to identify the specific influence of single nucleotide polymorphism (SNP) on iron-related quantitative traits (QT). Genetic effects on iron deposition at the disease level, SNP level, and their interactive effect were highlighted. RESULTS: Four strong SNP-QT associations were detected: rs602201-susceptibility of bilateral SN, rs198440-susceptibility of left SN, and rs7895403-susceptibility of left caudate head. Detailed analyses showed that: (1) significant iron deposition was exclusively found in bilateral SN in PD; (2) altered polymorphisms of the A allele/A- genotype of rs602201 and G allele/G- genotype of rs198440 and rs7895403 were more frequently observed in PD; (3) for rs602201, among all subjects, A- genotype carriers showed significantly increased iron content than TT genotype in bilateral SN; for rs198440 and rs7895403, G- carriers showed increased iron content than AA genotype in left SN and left caudate head, respectively; and (4) rs602201 exhibited significant SNP-by-disease interaction in bilateral SN. CONCLUSIONS: This study shows that rs602201 and rs198440 have a stimulative impact on nigral iron deposition in PD, which provides improved understanding of iron-related pathogenesis in PD, and specifically, that vulnerability to iron deposition in SN is genetic-based.

End-to-End Deep-Learning-Based Diagnosis of Benign and Malignant Orbital Tumors on Computed Tomography Images.

Determining the nature of orbital tumors is challenging for current imaging interpretation methods, which hinders timely treatment. This study aimed to propose an end-to-end deep learning system to automatically diagnose orbital tumors. A multi-center dataset of 602 non-contrast-enhanced computed tomography (CT) images were prepared. After image annotation and preprocessing, the CT images were used to train and test the deep learning (DL) model for the following two stages: orbital tumor segmentation and classification. The performance on the testing set was compared with the assessment of three ophthalmologists. For tumor segmentation, the model achieved a satisfactory performance, with an average dice similarity coefficient of 0.89. The classification model had an accuracy of 86.96%, a sensitivity of 80.00%, and a specificity of 94.12%. The area under the receiver operating characteristics curve (AUC) of the 10-fold cross-validation ranged from 0.8439 to 0.9546. There was no significant difference on diagnostic performance of the DL-based system and three ophthalmologists (p > 0.05). The proposed end-to-end deep learning system could deliver accurate segmentation and diagnosis of orbital tumors based on noninvasive CT images. Its effectiveness and independence from human interaction allow the potential for tumor screening in the orbit and other parts of the body.

White Matter Tract Injury by MRI in CADASIL Patients is Associated With Iron Accumulation.

BACKGROUND: Widespread white matter (WM) injury is a hallmark feature of cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). However, controversies about the mechanism of WM tract injury exist persistently. Excessive iron accumulation, frequently reported in CADASIL patients, might cause WM tract injury. PURPOSE: To test the association between iron accumulation and WM tract injury in CADASIL patients. STUDY TYPE: Retrospective. POPULATION: A total of 35 CADASIL patients (age = 50.4 ± 6.4, 62.9% female) and 48 healthy controls (age = 55.7 ± 8.0, 68.8% female). FIELD STRENGTH/SEQUENCE: Diffusion-weighted spin-echo echo-planar sequence; enhanced susceptibility-weighted angiography (ESWAN) gradient echo sequence on a 3 T scanner. ASSESSMENT: The phase images acquired by ESWAN were used to calculate quantitative susceptibility mapping (QSM). Iron accumulation was evaluated in deep gray matters using QSM. WM tract injury was quantified by diffusion metrics based on WM major tracts skeleton. We compared iron deposition between groups and analyzed the correlation between WM tract injury and iron deposition in regions showing significant differences from healthy controls. Exploratory analysis was carried out to investigate whether WM tract injury mediated the relationship between iron deposition and cognitive impairment evaluated by Mini-Mental State Examination (MMSE). STATISTICAL TESTS: General linear model (GLM), partial correlation, stepwise linear regression and mediation analysis were used. The threshold of statistical significance was set as p < 0.05. RESULTS: Compared with healthy controls, CADASIL patients had significantly increased iron deposition in the caudate and putamen. Aberrant iron deposition in these two regions was significantly associated with decreased WM fractional anisotropy (FA) (caudate, r = -0.373； putamen, r = - 0.421), and increased radial diffusivity (RD) (caudate, r = 0.372; putamen, r = 0.386). Furthermore, WM tract injury mediated the relationship between iron deposition and cognitive impairment. DATA CONCLUSION: Patients with CADASIL show increased iron deposition in the caudate and putamen that is correlated to WM tract injury, which may in turn mediate the association with cognitive impairment. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Quantitative susceptibility atlas construction in Montreal Neurological Institute space: towards histological-consistent iron-rich deep brain nucleus subregion identification.

Iron-rich deep brain nuclei (DBN) of the human brain are involved in various motoric, emotional and cognitive brain functions. The abnormal iron alterations in the DBN are closely associated with multiple neurological and psychiatric diseases. Quantitative susceptibility mapping (QSM) provides the spatial distribution of the magnetic susceptibility of human brain tissues. Compared to traditional structural imaging, QSM provides superiority for imaging the iron-rich DBN owing to the susceptibility difference existing between brain tissues. In this study, we constructed a Montreal Neurological Institute (MNI) space unbiased QSM human brain atlas via group-wise registration from 100 healthy subjects aged 19-29 years. The atlas construction process was guided by hybrid images that were fused from multi-modal magnetic resonance images (MRI). We named it as Multi-modal-fused magnetic Susceptibility (MuSus-100) atlas. The high-quality susceptibility atlas provides extraordinary image contrast between iron-rich DBN with their surroundings. Parcellation maps of DBN and their subregions that are highly related to neurological and psychiatric pathology were then manually labeled based on the atlas set with the assistance of an image border-enhancement process. Especially, the bilateral thalamus was delineated into 64 detailed subregions referring to the Schaltenbrand-Wahren stereotactic atlas. To our best knowledge, the histological-consistent thalamic nucleus parcellation map is well defined for the first time in the MNI space. Compared with existing atlases that emphasizing DBN parcellation, the newly proposed atlas outperforms on the task of atlas-guided individual brain image DBN segmentation both in accuracy and robustness. Moreover, we applied the proposed DBN parcellation map to conduct detailed identification of the pathology-related iron content alterations in subcortical nuclei for Parkinson's Disease (PD) patients. We envision that the MuSus-100 atlas can play a crucial role in improving the accuracy of DBN segmentation for the research of neurological and psychiatric disease progress and also be helpful for target planning in deep brain stimulation surgery.

Nigral Iron Deposition Influences Disease Severity by Modulating the Effect of Parkinson's Disease on Brain Networks.

BACKGROUND: In Parkinson's disease (PD), excessive iron deposition in the substantia nigra may exacerbate α-synuclein aggregation, facilitating the degeneration of dopaminergic neurons and their neural projection. OBJECTIVE: To investigate the interaction effect between nigral iron deposition and PD status on brain networks. METHODS: Eighty-five PD patients and 140 normal controls (NC) were included. Network function and nigral iron were measured using multi-modality magnetic resonance imaging. According to the median of nigral magnetic susceptibility of NC (0.095 ppm), PD and NC were respectively divided into high and low nigral iron group. The main and interaction effects were investigated by mixed effect analysis. RESULTS: The main effect of disease was observed in basal ganglia network (BGN) and visual network (VN). The interaction effect between nigral iron and PD status was observed in left inferior frontal gyrus and left insular lobe in BGN, as well as right middle occipital gyrus, right superior temporal gyrus, and bilateral cuneus in VN. Furthermore, multiple mediation analysis revealed that the functional connectivity of interaction effect clusters in BGN and medial VN partially mediated the relationship between nigral iron and Unified Parkinson's Disease Rating Scale II score. CONCLUSION: Our study demonstrates an interaction of nigral iron deposition and PD status on brain networks, that is, nigral iron deposition is associated with the change of brain network configuration exclusively when in PD. We identified a potential causal mediation pathway for iron to affect disease severity that was mediated by both BGN dysfunction and VN hyperfunction in PD.

Altered brain iron depositions from aging to Parkinson's disease and Alzheimer's disease: A quantitative susceptibility mapping study.

Brain iron deposition is a promising marker for human brain health, providing insightful information for understanding aging as well as neurodegenerations, e.g., Parkinson's disease (PD) and Alzheimer's disease (AD). To comprehensively evaluate brain iron deposition along with aging, PD-related neurodegeneration, from prodromal PD (pPD) to clinical PD (cPD), and AD-related neurodegeneration, from mild cognitive impairment (MCI) to AD, a total of 726 participants from July 2013 to December 2020, including 100 young adults, 189 old adults, 184 pPD, 171 cPD, 31 MCI and 51 AD patients, were included. Quantitative susceptibility mapping data were acquired and used to quantify regional magnetic susceptibility, and the resulting spatial standard deviations were recorded. A general linear model was applied to perform the inter-group comparison. As a result, relative to young adults, old adults showed significantly higher iron deposition with higher spatial variation in all of the subcortical nuclei (p < 0.01). pPD showed a high spatial variation of iron distribution in the subcortical nuclei except for substantia nigra (SN); and iron deposition in SN and red nucleus (RN) were progressively increased from pPD to cPD (p < 0.01). AD showed significantly higher iron deposition in caudate and putamen with higher spatial variation compared with old adults, pPD and cPD (p < 0.01), and significant iron deposition in SN compared with old adults (p < 0.01). Also, linear regression models had significances in predicting motor score in pPD and cPD (Rmean = 0.443, Ppermutation = 0.001) and cognition score in MCI and AD (Rmean = 0.243, Ppermutation = 0.037). In conclusion, progressive iron deposition in the SN and RN may characterize PD-related neurodegeneration, namely aging to cPD through pPD. On the other hand, extreme iron deposition in the caudate and putamen may characterize AD-related neurodegeneration.

The protective role of cigarette smoking against Parkinson's disease via moderation of the interaction between iron deposition in the nigrostriatal pathway and clinical symptoms.

Background: Although cigarette smoking is a risk factor for multiple disorders, it has long been thought to protect against Parkinson's disease (PD). Quantitative susceptibility mapping (QSM) is a novel magnetic resonance imaging (MRI)-based technique for assessing iron accumulation in vivo that has been widely applied in PD studies. This study aimed to investigate how cigarette smoking affects clinical performance of PD using quantified iron deposition as a proxy for PD pathology. Methods: In this observational study, we enrolled 35 male PD patients and 47 male healthy controls (HCs) and divided them into four groups. We performed an enhanced T2 star-weighted angiography (ESWAN) MRI sequence to measure the iron content of the nuclei within the nigrostriatal pathway. With the age and total intracranial volume (TIV) controlled as covariates, we performed inter-group comparisons of QSM values and moderation analyses for PD patients using smoking status and the smoking index (SI), respectively, as moderator variables. Results: The 2-way multivariate analysis of covariance (MANCOVA) results showed higher QSM values in the left red nucleus (P=0.024) in PD patients compared with those in HCs, and in the bilateral globi pallidi [left/right (L/R): P=0.009/0.003], substantia nigra pars compacta (SNc; L/R: P=0.001/0.037), and right substantia nigra pars reticulata (SNr; P=0.002) in non-smokers compared with smokers, with no marked interaction effect between PD and smoking status observed when applying the Bonferroni adjustment for multiple comparisons. Using cigarette smoking status and the SI as separate moderator variables, the moderation was shown up by a significant interaction effect in a disordinal and double-edged form. In our results, smoking-moderated protection for PD movement deficits emerged when PD was progressed. Among the affected deep brain nuclei, the nuclei most moderated by the impact of cigarette smoking on the interaction between brain iron and PD symptoms were the thalamus [smoking status associated with the Unified Parkinson's Disease Rating Scale (UPDRS) total score, P=0.04 (L); rigidity, P=0.03 (L); SI associated with UPDRS-III, P (L/R) =0.049/0.0497; rigidity, P (L/R) =0.01/0.02; bradykinesia, P (L/R) =0.048/0.04], the right red nucleus (SI associated with rigidity, P=0.04; bradykinesia, P=0.02), and the left SNc [smoking status associated with the Hoehn and Yahr (H&Y) stage, P=0.01]. Conclusions: This was the first study investigating the impacts of current cigarette smoking on PD using quantified iron deposition. Our study confirmed the protective role of cigarette smoking against PD, consistent with the findings of previous studies. Furthermore, neuroprotection was present only when the PD pathology had progressed to a certain extent. In the interaction between iron deposition and clinical PD symptoms, our findings suggest that the thalamus, red nucleus, and SNc are likely to be the most affected nuclei moderated by cigarette smoking.

A Clinical Semantic and Radiomics Nomogram for Predicting Brain Invasion in WHO Grade II Meningioma Based on Tumor and Tumor-to-Brain Interface Features.

BACKGROUND: Brain invasion in meningioma has independent associations with increased risks of tumor progression, lesion recurrence, and poor prognosis. Therefore, this study aimed to construct a model for predicting brain invasion in WHO grade II meningioma by using preoperative MRI. METHODS: One hundred seventy-three patients with brain invasion and 111 patients without brain invasion were included. Three mainstream features, namely, traditional semantic features and radiomics features from tumor and tumor-to-brain interface regions, were acquired. Predictive models correspondingly constructed on each feature set or joint feature set were constructed. RESULTS: Traditional semantic findings, e.g., peritumoral edema and other four features, had comparable performance in predicting brain invasion with each radiomics feature set. By taking advantage of semantic features and radiomics features from tumoral and tumor-to-brain interface regions, an integrated nomogram that quantifies the risk factor of each selected feature was constructed and had the best performance in predicting brain invasion (area under the curve values were 0.905 in the training set and 0.895 in the test set). CONCLUSIONS: This study provided a clinically available and promising approach to predict brain invasion in WHO grade II meningiomas by using preoperative MRI.

Substantia nigra iron affects functional connectivity networks modifying working memory performance in younger adults.

Brain iron affects working memory (WM) but the impact of iron content in deep grey matter nuclei on WM networks is unknown. We aimed to test whether deep grey matter nuclei iron concentration can affect resting-state functional connectivity (rsFC) within brain networks modifying WM performance. An N-back WM paradigm was applied in a hundred healthy younger adults. The participants then underwent a resting-state functional magnetic resonance imaging (fMRI) for brain network analysis and quantitative susceptibility mapping (QSM) imaging for assessment of deep grey matter nuclei iron concentration. Higher substantia nigra (SN) iron concentration was associated with lower rsFC between SN and brain regions of the temporal/frontal lobe but with better WM performance after controlling for age, gender and education. A follow-up mediation analysis also indicated that functional connectivity may mediate the link between SN iron and WM performance. Our results suggest that high SN iron concentration may affect communication between the SN and temporal/frontal lobe and is associated with strengthened WM performance in younger adults.

Serum Ceruloplasmin Depletion is Associated With Magnetic Resonance Evidence of Widespread Accumulation of Brain Iron in Parkinson's Disease.

BACKGROUND: Excessive iron accumulation is one of the main pathogeneses of Parkinson's disease (PD). Ceruloplasmin plays an important role in keeping the iron homoeostasis. PURPOSE: To explore the association between serum ceruloplasmin depletion and subcortical iron distribution in PD. STUDY TYPE: Prospective. POPULATION: One hundred and twenty-one normal controls, 34 PD patients with low serum ceruloplasmin (PD-LC), and 28 patients with normal serum ceruloplasmin (PD-NC). SEQUENCE: Enhanced susceptibility-weighted angiography (ESWAN) on a 3 T scanner. ASSESSMENT: Quantitative susceptibility mapping was employed to quantify the regional iron content by using a semi-automatic method. Serum ceruloplasmin concentration was measured from peripheral blood sample. Clinical assessments were conducted by a neurologist. STATISTICAL TESTS: General linear model was used to compare the intergroup difference of region iron distribution among groups, and the statistics was adjusted by Bonferroni method (P < 0.01). Partial correlation analysis was used to detect the association between regional iron distribution and serum ceruloplasmin concentration (P < 0.05). RESULTS: Compared with normal controls, significant iron accumulation in substantia nigra, putamen, and red nucleus was observed in PD-LC, while the only region showing significant iron accumulation was SN in PD-NC. Between PD-NC and PD-LC, the iron accumulation in putamen remained significantly different, which had a negative correlation with serum ceruloplasmin in whole PD patients (r = -0.338, P = 0.008). DATA CONCLUSION: Nigral iron accumulation characterizes PD patients without significant association with serum ceruloplasmin. Differentially, when PD patients appear with reduced serum ceruloplasmin, more widespread iron accumulation would be expected with additionally involving putamen and red nucleus. All these findings provide insightful evidence for the abnormal iron metabolism behind the ceruloplasmin depletion in PD. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: 2.

Potential role of m6A RNA methylation regulators in osteosarcoma and its clinical prognostic value.

BACKGROUND: Osteosarcoma is a disease with high mortality in children and adolescents, and metastasis is one of the important clinical features of osteosarcoma. N6-Methyladenosine (m6A) is the most abundant methylation modification in mRNA, which is regulated by m6A regulators. It is reported that it is related to the occurrence and development of tumors. However, the mechanism of its action in osteosarcoma is rarely known. The purpose of this study was to identify the potential role of m6A regulatory factor in osteosarcoma and its clinical prognostic value. METHODS: Here, we used The Cancer Genome Atlas (TCGA) to comprehensively analyze the relationship between m6A regulatory factors and osteosarcoma (metastasis group and non-metastasis group). We analyzed their survival relationship and analyzed all the m6A regulatory factors in TCGA tumor data set by using the univariate Cox proportional hazard regression model. Finally, we selected two survival-related methylation regulators (FTO and IGF2BP2) as risk gene signature. RESULTS: According to the median risk, patients were divided into low-risk group and high-risk group. Multivariate Cox regression analysis showed that these two risk genes were considered to be the key factors independently predicting the prognosis of patients with osteosarcoma. In addition, we verified their characteristics with gene expression omnibus (GEO) DataSets and confirmed that they are related to tumor and immune-related signaling pathways through gene set enrichment analysis (GESA) and immune infiltration analysis. CONCLUSIONS: In conclusion, m6A regulators might play an important role in the metastasis of osteosarcoma and have potential important value for the prognosis and treatment strategy of osteosarcoma patients.

The Usefulness of Imaging Quantification in Discriminating Non-Calcified Pulmonary Hamartoma From Adenocarcinoma.

BACKGROUND: Patients with non-calcified hamartoma were more susceptible to surgery or needle biopsy for the tough discrimination from lung adenocarcinoma. Radiomics have the ability to quantify the lesion features and potentially improve disease diagnosis. Thus, this study aimed to discriminate non-calcified hamartoma from adenocarcinoma by employing imaging quantification and machine learning. METHODS: Forty-two patients with non-calcified hamartoma and 49 patients with adenocarcinoma were retrospentation; Manual lesion segmentation, feature quantification (e.g., texture features), and artificial neural network were performed consecutively. Independent t-test was used to conduct the inter-group comparisons of those imaging features. Receiver operating characteristic curve was performed to investigate the discriminating efficacy. RESULTS: Significantly higher contrast, cluster prominence, cluster shade, dissimilarity, energy, and entropy in non-calcified hamartoma were observed compared with lung adenocarcinoma. Texture-grey-level co-occurrence matrix showed a well discrimination between non-calcified hamartoma and adenocarcinoma as the detection sensitivity, specificity, accuracy, and the area under the curve were 87.22% ± 9.07%, 82.64% ± 8.07%, 85.11% ± 5.40%, and 0.942, respectively. CONCLUSION: Quantifying imaging features is a potentially useful tool for clinical diagnosis. This study demonstrated that non-calcified hamartoma has a heterogeneous distribution of attenuations probably resulting from its complex organizations. Based on this property, imaging quantification could improve discrimination of non-calcified hamartoma from adenocarcinoma.

Asymmetrical nigral iron accumulation in Parkinson's disease with motor asymmetry: an explorative, longitudinal and test-retest study.

Parkinson's disease (PD) is commonly characterized by asymmetrical motor impairment. This study aimed to clarify the iron distributions in PD patients with significant motor asymmetry and their longitudinal alterations. This study included 123 PD patients and 121 normal controls. Thirty-eight PD patients were revisited. PD patients with significant motor asymmetry were identified by using an objective criterion. Inter-group, inter-hemisphere and inter-visit differences of regional tissue susceptibility were analyzed. Iron accumulation in dominantly and non-dominantly affected substantia nigra (SN) were observed in PD patients with motor asymmetry compared with normal controls (p < 0.005, Bonferroni corrected). Iron accumulation in the dominantly affected SN was significantly higher than that in the non-dominantly affected SN (p < 0.01, Bonferroni corrected). After follow-up, time effect on the iron content in SN was observed, directing to decrease in PD patients with motor asymmetry without hemispherical difference (p < 0.05). In conclusion, asymmetrical iron accumulation in SN was associated with the motor asymmetry in PD at baseline, while along the disease evolution iron content in SN became longitudinally decreased. All these findings provide new evidence for PD pathogenesis that the abnormal iron metabolism in SN is complicated and not always unidirectional.

A New Application of Multimodality Radiomics Improves Diagnostic Accuracy of Nonpalpable Breast Lesions in Patients with Microcalcifications-Only in Mammography.

BACKGROUND The aim of this study was to assess a radiomic scheme that combines image features from digital mammography and dynamic contrast-enhanced MRI to improve classification accuracy of nonpalpable breast lesion (NBL) with Breast Imaging-Reporting and Data System (BI-RADS) 3-5 microcalcifications-only in mammography. MATERIAL AND METHODS This retrospective study was approved by the Internal Research Review and Ethical Committee of our hospital. We included 81 patients who underwent a three-dimensional digital breast X-ray wire positioning for local resection between October 2012 and November 2016. All patients underwent breast MRI and mammography before the treatment, and all obtained pathological confirmation. According to the pathological results, 41 patients with benign lesions were assigned to the benign group and 40 patients with malignant lesions were assigned to the malignant group. We used the random forest algorithm to select significant features and to test the single and multimodal classifiers using the Leave-One-Out-Cross-Validation method. An area under the receiver operating characteristic curve was also used to evaluate its discriminating performance. RESULTS The multimodal classifier achieved AUC of 0.903, with a sensitivity of 82.5% and a specificity of 80.48%, which was better than any single modality. CONCLUSIONS Multimodal radiomics classification shows promising power in discriminating malignant lesions from benign lesions in NBL patients with BI-RADS 3-5 microcalcifications-only in mammography.