R2* relaxometry analysis for mapping of white matter alteration in Parkinson's disease with mild cognitive impairment

Diagnostic Accuracy of Machine Learning-Assisted MRI for Mild Cognitive Impairment in Parkinson's Disease: A Systematic Review and Meta-Analysis

To evaluate the diagnostic accuracy of machine learning-assisted magnetic resonance imaging (MRI) in detecting cognitive impairment among Parkinson's disease (PD) patients through a systematic review and meta-analysis. We systematically searched for studies that applied machine learning algorithms to MRI data for diagnosing PD with mild cognitive impairment (PD-MCI). Data were extracted and synthesized to calculate pooled sensitivity, specificity, positive likelihood ratio (PLR) and negative diagnostic likelihood ratio (NLR), and diagnostic odds ratios (DOR). A bivariate random-effects model and summary receiver operating characteristic (SROC) curves were employed for statistical analysis. The quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) instrument. The publication bias was investigated through Deeks' funnel plot. All statistical analyses were conducted using Stata 14.0. The pooled sensitivity and specificity for diagnosing PD-MCI using machine learning-assisted MRI were 0.82 (95% CI: 0.75-0.87) and 0.81 (95% CI: 0.73-0.87), respectively. The PLR was 4.28 (95% CI: 2.93-6.27), and the NLR was 0.23 (95% CI: 0.16-0.32), indicating a high diagnostic accuracy. The area under the curve (AUC) for the SROC was 0.85 (95% CI: 0.82-0.88). Quality assessment using the QUADAS-2 tool showed a predominantly low risk of bias among the studies, and the Deeks' funnel plot suggested no significant publication bias (p=0.30). In summary, the MRI combined with machine learning for diagnosing PD-MCI achieved high accuracy with the pooled sensitivity of 82% and specificity of 81%.

Associations Between Cortical Iron Accumulation and Memory in Patients With Amnestic Mild Cognitive Impairment and in Cognitively Normal Individuals

BACKGROUND AND PURPOSE

Brain iron accumulation is recognized as a cause and therapeutic target in Alzheimer's disease (AD). We investigated the differences in both volume and iron accumulation between cognitively normal (CN) older adults and patients with amnestic mild cognitive impairment (aMCI). Additionally, we assessed which combination of these measures best explains the group differences in visual and verbal memory performance.

MATERIALS AND METHODS

We retrospectively analyzed data from 48 patients with aMCI and 33 age-matched CN individuals. Structural differences were investigated using voxel-based comparisons of T1-weighted magnetic resonance images. Differences in iron accumulation were investigated using voxel-based comparisons of quantitative susceptibility mapping (QSM) images. Subsequently, significant clusters from these voxel-based analyses (amygdala, posterior cingulate cortex, precuneus, lateral occipital cortex, and pericalcarine cortex) were entered into a stepwise regression to predict verbal and visual memory scores, while accounting for age, sex, and education as covariates.

RESULTS

In comparison to CN, patients with aMCI had significantly lower scores in both verbal and visual memory tests (p < 0.001). The T1-weighted voxel-based morphometry (VBM) results showed significant hippocampal atrophy in the aMCI group relative to CN individuals. The QSM-VBM results showed increased iron accumulation in the amygdala, posterior cingulate cortex, precuneus, lateral occipital cortex, and pericalcarine cortex (FWE-corrected p < 0.05). Lower hippocampal volume (B = 2015.91, SE = 469.61, p < 0.001) and higher posterior cingulate cortex susceptibility (B = -189.63 SE = 89.11, p = 0.037) were significant predictors of verbal memory. For visual memory, higher lateral occipital susceptibility (B = -659. 96, SE = 253.03, p = 0.011) was significant imaging predictor.

CONCLUSIONS

These results suggest that iron accumulates in regions where atrophy has not yet occurred, suggesting that iron may serve as an earlier imaging marker of neurodegeneration compared to volume atrophy. Further studies are needed to investigate the longitudinal relationship between brain volume and iron accumulation during cognitive decline.

Evaluation of iron deposition in diabetic kidney disease using the kidney-to-muscle signal intensity ratio on routine MRI T2WI sequences

OBJECTIVE

The T2* technique in Blood Oxygen Level Dependent Magnetic Resonance Imaging (BOLD-MRI) has been established as a non-invasive standard for quantifying tissue iron levels. This study aims to assess the feasibility of obtaining quantitative iron-sensitive information from conventional MRI T2-weighted imaging (T2WI) sequences, typically used for anatomical rather than quantitative assessments, and to explore its potential as a routine monitoring tool for renal iron levels in diabetic kidney disease (DKD).

METHODS

A total of 142 patient imaging data from renal MRI scans were retrospectively analyzed. We measured the kidney and psoas major muscle signal intensity on T2WI sequences and calculated the kidney-to-muscle signal intensity ratio (K/M-SIR) to determine differences across patient groups. Relevant laboratory indices were collected to analyze the correlation between K/M-SIR and laboratory markers.

RESULTS

We included 42 clinically confirmed DKD patients, 47 patients with diabetes but no DKD, and 53 healthy subjects. The K/M-SIR was 2.66 ± 0.49 in DKD patients, 2.94 ± 0.51 in diabetic patients without DKD, and 2.95 ± 0.55 in healthy subjects. There were statistically significant differences in K/M-SIR between DKD patients and healthy subjects (p = 0.008) and between DKD patients and diabetic patients without DKD (p = 0.009). K/M-SIR values were negatively correlated with laboratory indices such as glycated hemoglobin (HbA1c), microalbuminuria (MAU), albumin-to-creatinine ratio (ACR), and 24-hour urinary protein (24 h UP).

CONCLUSION

The kidney-to-muscle signal intensity ratio (K/M-SIR) derived from routine MRI T2WI sequences is valuable for diagnosing DKD and may serve as a reliable non-invasive marker for assessing renal iron deposition in DKD, potentially aiding in the diagnosis and monitoring of DKD severity.

Quantitative susceptibility mapping analyses of white matter in Parkinson's disease using susceptibility separation technique

INTRODUCTION

To apply susceptibility separation on quantitative susceptibility mapping (QSM) images of Parkinson's disease (PD) patients to obtain more accurate images and gain pathophysiological insights.

METHODS

This retrospective study included subjects who underwent head MRI, including QSM between March 2016 and March 2018. Patients with PD were categorized as having mild cognitive impairment (PD-MCI), or normal cognition (PD-CN); healthy controls (HC) were also enrolled. Susceptibility separation generated positive (QSM+) and negative susceptibility (QSM-) labels. Voxel-based whole-brain susceptibility and atlas-based susceptibility were compared among groups on white matter. Correlations between susceptibility and Montreal Cognitive Assessment (MoCA) scores were analyzed.

RESULTS

Overall, 65 subjects (mean age 72 years ±6, 35 men) were included. White-matter regions with significant (P < 0.05) group differences were found for QSM+ (HC > PD-MCI, PD-CN > PD-MCI) and QSM- (PD-MCI > HC, PD-MCI > PD-CN). In the atlas-based analyses, PD-MCI exhibited lower QSM + values (vs. HC; P = 0.002, vs. PD-CN; P = 0.001), and higher QSM-values (vs. HC; P = 0.02, vs. PD-CN; P = 0.03) in the genu of corpus callosum (gCC). QSM+ and QSM-showed significant positive and negative correlations with MoCA (P < 0.05). In the gCC, partial correlation analyses revealed a positive correlation between QSM+ and MoCA (R = 0.458, P < 0.001) and a negative correlation between QSM- and MoCA (R = -0.316, P = 0.01).

CONCLUSION

QSM utilizing susceptibility separation is valuable for assessing white matter in PD patients, where nerve fiber loss potentially influences cognitive function.

Iron Deposition in Parkinson's Disease: A Mini-Review

Iron deposition is crucial pathological changes observed in patients with Parkinson's disease (PD). Recently, scientists have actively explored therapeutic approaches targeting iron deposition in PD. However, several clinical studies have failed to yield consistent results. In this review, we provide an overview of iron deposition in PD, from both basic research and clinical perspectives. PD patients exhibit abnormalities in various iron metabolism-related proteins, leading to disruptions in iron distribution, transport, storage, and circulation, ultimately resulting in iron deposition. Excess iron can induce oxidative stress and iron-related cell death, and exacerbate mitochondrial dysfunction, contributing to the progression of PD pathology. Magnetic resonance imaging studies have indicated that the characteristics of iron deposition in the brains of PD patients vary. Iron deposition correlates with the clinical symptoms of PD, and patients with different disease courses and clinical presentations display distinct patterns of iron deposition. These iron deposition patterns may contribute to PD diagnosis. Iron deposition is a promising target for PD treatment. However, further research is required to elucidate the underlying mechanisms and their impacts on PD.

Case report: Clinically mild encephalitis/encephalopathy with a reversible splenial lesion: an autopsy case

Clinically mild encephalitis/encephalopathy with a reversible splenial lesion is a clinicoradiological syndrome characterized by transient neuropsychiatric symptoms and hyperintensity of the splenium of the corpus callosum on diffusion-weighted MRI. Although intramyelinic edema and inflammatory cell infiltration can be predicted by MRI, the pathology of the splenium of the corpus callosum remains unknown. We encountered a case of clinically mild encephalitis/encephalopathy with a reversible splenial lesion and hypoglycemia in a patient who died of sepsis, and an autopsy was performed. The postmortem pathological findings included intramyelinic edema, myelin pallor, loss of fibrous astrocytes, microglial reactions, and minimal lymphocytic infiltration in the parenchyma. Based on these findings, transient demyelination following cytotoxic edema in the splenium of corpus callosum was strongly considered a pathogenesis of "clinically mild encephalitis/encephalopathy with a reversible splenial lesion" associated with hypoglycemia, and it could be generalized for the disease associated with the other causes. As cytotoxic edema could be the central pathology of the disease, the recently proposed term cytotoxic lesions of the corpus callosum may be applicable to this syndrome.

Current and Future Developments in Imaging and Treatment of White Matter Disease: A Systematic Review

The elderly often suffer from "mild" dementia due to white matter disease, which is another name for repeated brain infarctions. The degeneration of white matter, which links various parts of the brain to the spinal cord, is the root cause of this disorder, which develops with age. Dementia, imbalance, and movement problems are symptoms of this degenerative disease that worsen with age. This research's goal is to study current therapy options and identify methods for early diagnosis of white matter illness. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement for meta-analyses and systematic reviews served as the basis for our literature review. Results from the search in ScienceDirect and Medline/Pubmed led to the finalization of 33 studies. The complex relationship between white matter hyperintensities (WMHs) and neurological disorders is the subject of this comprehensive review, which sheds light on the varied terrain of WMH studies by highlighting their consequences and developing evaluation techniques.

White matter changes in Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disease after Alzheimer's disease (AD). It is characterized by a progressive loss of dopaminergic neurons in the substantia nigra pars compacta (SNc) and the formation of Lewy bodies (LBs). Although PD is primarily considered a gray matter (GM) disease, alterations in white matter (WM) have gained increasing attention in PD research recently. Here we review evidence collected by magnetic resonance imaging (MRI) techniques which indicate WM abnormalities in PD, and discuss the correlations between WM changes and specific PD symptoms. Then we summarize transcriptome and genome studies showing the changes of oligodendrocyte (OLs)/myelin in PD. We conclude that WM abnormalities caused by the changes of myelin/OLs might be important for PD pathology, which could be potential targets for PD treatment.

Diagnostic value of combined magnetic resonance imaging techniques in the evaluation of Parkinson disease

Background

The incidence of Parkinson disease (PD) has been increasing each year. The development of new magnetic resonance imaging (MRI) technology can help understand its pathogenesis and identify more effective imaging-based biological indicators.

Methods

The clinical and MRI imaging data of 40 patients with PD and 40 healthy controls were analyzed. All participants underwent susceptibility-weighted imaging (SWI), neuromelanin-sensitive magnetic resonance imaging (NM-MRI), and T2*mapping sequence examination. The diagnostic value of single and combined multiparameter indicators was analyzed using the receiver operating characteristic curve.

Results

Compared with the healthy control group, the PD group showed significant differences in the disappearance of bilateral "swallow tail sign", the distribution volume of melanocytes in the substantia nigra and the smaller volume in the bilateral substantia nigra, the maximum signal of the locus coeruleus and the smaller and average volume in the bilateral substantia nigra, and the values of T2* and R2* in the bilateral substantia nigra (P<0.01). The maximum and smaller value and the average value of the bilateral locus coeruleus signal were negatively correlated with the disease course duration (P<0.05), and the smaller distribution volume of the melanin neurons in the bilateral substantia nigra was negatively correlated with Hoehn and Yahr (H-Y) grade (P<0.05). In the joint diagnosis with multiple indicators, some composite parameters were found to be negatively correlated with H-Y grading (P<0.05), while others were negatively correlated with disease course duration (P<0.05). Joint use of multiple parameter indicators greatly improved diagnostic efficacy [area under the curve (AUC) =0.958].

Conclusions

The distribution volume of melanin in substantia nigra and the maximum value of locus coeruleus signal may be the biological imaging indicators for the early diagnosis, severity, and follow-up evaluation of PD. Compared with a single indicator, composite indicators used in combination with multiple techniques have a significantly better diagnostic efficacy for PD.

Assessing white matter microstructural changes in idiopathic normal pressure hydrocephalus using voxel-based R2* relaxometry analysis

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.

Application value of multiparametric MRI for evaluating iron deposition in the substantia nigra in Parkinson's disease

Objective

This study aimed to investigate the application value of multi-parametric magnetic resonance imaging (MRI) in the diagnosis of iron deposition in the substantia nigra dense zone in Parkinson's disease (PD) and to evaluate the diagnostic value of the correlation among multi-parametric imaging indicators, clinical stage, and disease duration.

Materials and methods

Thirty-six patients with clinically confirmed PD and 36 healthy controls were enrolled. The disease course was recorded, and PD severity was graded using the Hoehn-Yahr (H-Y) scale. All subjects underwent magnetic sensitivity weighted imaging (SWI), neuromelanin magnetic resonance imaging (NM-MRI), and a T2^*mapping sequence. Based on the fusion of the NM-MRI and SWI amplitude maps, phase maps, and T2^*MAPPING value maps, NM-MRI was used to delineate the dense zone of the substantia nigra, which was divided into three sub-regions: upper, middle, and lower. In this way, the amplitude, phase, and R2^* values of each sub-region and the average value of the sum of the three sub-regions were obtained simultaneously in the SWI amplitude, phase, and T2^*MAPPING maps. The multi-parameter imaging indices were compared between the two groups, and the correlation between them and clinical indices was evaluated in the PD group.

Results

The upper (amplitude, phase value, R2^* value), middle, and lower (amplitude) right substantia nigra compact zones were significantly different between the PD and control groups. The upper (phase value, R2^* value) and middle (amplitude) areas of the left substantia nigra compact zone were also significantly different between the two groups (all P < 0.05). The mean values (amplitude, phase value, R2^* value) of the right substantia nigra densification zone and the mean values (phase value) of the left substantia nigra densification zone were also significantly different (all P < 0.05). Amplitudes in the middle and lower parts of the right substantia nigra dense zone were negatively correlated with the H-Y grade (middle: r = -0.475, P = 0.003; lower: r = -0.331, P = 0.049). Amplitudes of the middle and lower parts of the dense zone of the left substantia nigra were negatively correlated with the H-Y grade (middle: r = -0.342, P = 0.041; lower: r = -0.399, P = 0.016). The average amplitude of the right substantia nigra compact zone was negatively correlated with the H-Y grade (r = -0.367, P = 0.027). The average R2^* value of the compact zone of the left substantia nigra was positively correlated with the H-Y grade (r = 0.345, P = 0.040).

Conclusion

Multiparametric MRI sequence examination has application value in the evaluation of iron deposition in the dense zone of the substantia nigra in PD. Combined with NM-MRI, fusion analysis is beneficial for accurately locating the substantia nigra compact zone and quantitatively analyzing the iron deposition in different sub-regions. Quantitative iron deposition in the middle and lower parts of the substantia nigra dense zone may become an imaging biological indicator for early diagnosis, severity evaluation, and follow-up evaluation of PD and is thus conducive for clinical diagnosis and treatment evaluation.

Quantitative susceptibility mapping as an imaging biomarker for Alzheimer’s disease: The expectations and limitations

Alzheimer’s disease (AD) is the most common type of dementia and a distressing diagnosis for individuals and caregivers. Researchers and clinical trials have mainly focused on β-amyloid plaques, which are hypothesized to be one of the most important factors for neurodegeneration in AD. Meanwhile, recent clinicopathological and radiological studies have shown closer associations of tau pathology rather than β-amyloid pathology with the onset and progression of Alzheimer’s symptoms. Toward a biological definition of biomarker-based research framework for AD, the 2018 National Institute on Aging–Alzheimer’s Association working group has updated the ATN classification system for stratifying disease status in accordance with relevant pathological biomarker profiles, such as cerebral β-amyloid deposition, hyperphosphorylated tau, and neurodegeneration. In addition, altered iron metabolism has been considered to interact with abnormal proteins related to AD pathology thorough generating oxidative stress, as some prior histochemical and histopathological studies supported this iron-mediated pathomechanism. Quantitative susceptibility mapping (QSM) has recently become more popular as a non-invasive magnetic resonance technique to quantify local tissue susceptibility with high spatial resolution, which is sensitive to the presence of iron. The association of cerebral susceptibility values with other pathological biomarkers for AD has been investigated using various QSM techniques; however, direct evidence of these associations remains elusive. In this review, we first briefly describe the principles of QSM. Second, we focus on a large variety of QSM applications, ranging from common applications, such as cerebral iron deposition, to more recent applications, such as the assessment of impaired myelination, quantification of venous oxygen saturation, and measurement of blood– brain barrier function in clinical settings for AD. Third, we mention the relationships among QSM, established biomarkers, and cognitive performance in AD. Finally, we discuss the role of QSM as an imaging biomarker as well as the expectations and limitations of clinically useful diagnostic and therapeutic implications for AD.