Diagnosing Parkinson's disease by combining neuromelanin and iron imaging features using an automated midbrain template approach

Iron deposition in subcortical nuclei of Parkinson's disease: A meta-analysis of quantitative iron-sensitive magnetic resonance imaging studies

BACKGROUND

Iron deposition plays a crucial role in the pathophysiology of Parkinson's disease (PD), yet the distribution pattern of iron deposition in the subcortical nuclei has been inconsistent across previous studies. We aimed to assess the difference patterns of iron deposition detected by quantitative iron-sensitive magnetic resonance imaging (MRI) between patients with PD and patients with atypical parkinsonian syndromes (APSs), and between patients with PD and healthy controls (HCs).

METHODS

A systematic literature search was conducted on PubMed, Embase, and Web of Science databases to identify studies investigating the iron content in PD patients using the iron-sensitive MRI techniques (R2* and quantitative susceptibility mapping [QSM]), up until May 1, 2023. The quality assessment of case-control and cohort studies was performed using the Newcastle-Ottawa Scale, whereas diagnostic studies were assessed using the Quality Assessment of Diagnostic Accuracy Studies-2. Standardized mean differences and summary estimates of sensitivity, specificity, and area under the curve (AUC) were calculated for iron content, using a random effects model. We also conducted the subgroup-analysis based on the MRI sequence and meta-regression.

RESULTS

Seventy-seven studies with 3192 PD, 209 multiple system atrophy (MSA), 174 progressive supranuclear palsy (PSP), and 2447 HCs were included. Elevated iron content in substantia nigra (SN) pars reticulata (P <0.001) and compacta (P <0.001), SN (P <0.001), red nucleus (RN, P <0.001), globus pallidus (P <0.001), putamen (PUT, P = 0.009), and thalamus (P = 0.046) were found in PD patients compared with HCs. PD patients showed lower iron content in PUT (P <0.001), RN (P = 0.003), SN (P = 0.017), and caudate nucleus (P = 0.027) than MSA patients, and lower iron content in RN (P = 0.001), PUT (P <0.001), globus pallidus (P = 0.004), SN (P = 0.015), and caudate nucleus (P = 0.001) than PSP patients. The highest diagnostic accuracy distinguishing PD from HCs was observed in SN (AUC: 0.85), and that distinguishing PD from MSA was found in PUT (AUC: 0.90). In addition, the best diagnostic performance was achieved in the RN for distinguishing PD from PSP (AUC: 0.84).

CONCLUSION

Quantitative iron-sensitive MRI could quantitatively detect the iron content of subcortical nuclei in PD and APSs, while it may be insufficient to accurately diagnose PD. Future studies are needed to explore the role of multimodal MRI in the diagnosis of PD.

REGISTRISION

PROSPERO; CRD42022344413.

PENCIL imaging: A novel approach for neuromelanin sensitive MRI in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is associated with the loss of neuromelanin (NM) and increased iron in the substantia nigra (SN). Magnetization transfer contrast (MTC) is widely used for NM visualization but has limitations in brain coverage and scan time. This study aimed to develop a new approach called Proton-density Enhanced Neuromelanin Contrast in Low flip angle gradient echo (PENCIL) imaging to visualize NM in the SN.

METHODS

This study included 30 PD subjects and 50 healthy controls (HCs) scanned at 3T. PENCIL and MTC images were acquired. NM volume in the SN pars compacta (SNpc), normalized image contrast (Cnorm), and contrast-to-noise ratio (CNR) were calculated. The change of NM volume in the SNpc with age was analyzed using the HC data. A group analysis compared differences between PD subjects and HCs. Receiver operating characteristic (ROC) analysis and area under the curve (AUC) calculations were used to evaluate the diagnostic performance of NM volume and CNR in the SNpc.

RESULTS

PENCIL provided similar visualization and structural information of NM compared to MTC. In HCs, PENCIL showed higher NM volume in the SNpc than MTC, but this difference was not observed in PD subjects. PENCIL had higher CNR, while MTC had higher Cnorm. Both methods revealed a similar pattern of NM volume in SNpc changes with age. There were no significant differences in AUCs between NM volume in SNpc measured by PENCIL and MTC. Both methods exhibited comparable diagnostic performance in this regard.

CONCLUSIONS

PENCIL imaging provided improved CNR compared to MTC and showed similar diagnostic performance for differentiating PD subjects from HCs. The major advantage is PENCIL has rapid whole-brain coverage and, when using STAGE imaging, offers a one-stop quantitative assessment of tissue properties.

Increased iron in the substantia nigra pars compacta identifies patients with early Parkinson'sdisease: A 3T and 7T MRI study

Degeneration in the substantia nigra (SN) pars compacta (SNc) underlies motor symptoms in Parkinson's disease (PD). Currently, there are no neuroimaging biomarkers that are sufficiently sensitive, specific, reproducible, and accessible for routine diagnosis or staging of PD. Although iron is essential for cellular processes, it also mediates neurodegeneration. MRI can localize and quantify brain iron using magnetic susceptibility, which could potentially provide biomarkers of PD. We measured iron in the SNc, SN pars reticulata (SNr), total SN, and ventral tegmental area (VTA), using quantitative susceptibility mapping (QSM) and R2* relaxometry, in PD patients and age-matched healthy controls (HCs). PD patients, diagnosed within five years of participation and HCs were scanned at 3T (22 PD and 23 HCs) and 7T (17 PD and 21 HCs) MRI. Midbrain nuclei were segmented using a probabilistic subcortical atlas. QSM and R2* values were measured in midbrain subregions. For each measure, groups were contrasted, with Age and Sex as covariates, and receiver operating characteristic (ROC) curve analyses were performed with repeated k-fold cross-validation to test the potential of our measures to classify PD patients and HCs. Statistical differences of area under the curves (AUCs) were compared using the Hanley-MacNeil method (QSM versus R2*; 3T versus 7T MRI). PD patients had higher QSM values in the SNc at both 3T (padj = 0.001) and 7T (padj = 0.01), but not in SNr, total SN, or VTA, at either field strength. No significant group differences were revealed using R2* in any midbrain region at 3T, though increased R2* values in SNc at 7T MRI were marginally significant in PDs compared to HCs (padj = 0.052). ROC curve analyses showed that SNc iron measured with QSM, distinguished early PD patients from HCs at the single-subject level with good diagnostic accuracy, using 3T (mean AUC = 0.83, 95 % CI = 0.82-0.84) and 7T (mean AUC = 0.80, 95 % CI = 0.79-0.81) MRI. Mean AUCs reported here are from averages of tests in the hold-out fold of cross-validated samples. The Hanley-MacNeil method demonstrated that QSM outperforms R2* in discriminating PD patients from HCs at 3T, but not 7T. There were no significant differences between 3T and 7T in diagnostic accuracy of QSM values in SNc. This study highlights the importance of segmenting midbrain subregions, performed here using a standardized atlas, and demonstrates high accuracy of SNc iron measured with QSM at 3T MRI in identifying early PD patients. QSM measures of SNc show potential for inclusion in neuroimaging diagnostic biomarkers of early PD. An MRI diagnostic biomarker of PD would represent a significant clinical advance.

Automatic Segmentation and Quantification of Nigrosome-1 Neuromelanin and Iron in MRI: A Candidate Biomarker for Parkinson's Disease

BACKGROUND

There is a lack of automated tools for the segmentation and quantification of neuromelanin (NM) and iron in the nigrosome-1 (N1). Existing tools evaluate the N1 sign, i.e., the presence or absence of the "swallow-tail" in iron-sensitive MRI, or globally analyze the MRI signal in an area containing the N1, without providing a volumetric delineation.

PURPOSE

Present an automated method to segment the N1 and quantify differences in N1's NM and iron content between Parkinson's disease (PD) patients and healthy controls (HCs). Study whether N1 degeneration is clinically related to PD and could be used as a biomarker of the disease.

STUDY TYPE

Prospective.

SUBJECTS

Seventy-one PD (65.3 ± 10.3 years old, 34 female/37 male); 30 HC (62.7 ± 7.8 years old, 17 female/13 male).

FIELD STRENGTH/SEQUENCE

3 T Anatomical T1-weighted MPRAGE, NM-MRI T1-weighted gradient with magnetization transfer, susceptibility-weighted imaging (SWI).

ASSESSMENT

N1 was automatically segmented in SWI images using a multi-image atlas, populated with healthy N1 structures manually annotated by a neurologist. Relative NM and iron content were quantified and their diagnostic performance assessed and compared with the substantia nigra pars compacta (SNc). The association between image parameters and clinically relevant variables was studied.

STATISTICAL TESTS

Nonparametric tests were used (Mann-Whitney's U, chi-square, and Friedman tests) at P = 0.05.

RESULTS

N1's relative NM content decreased and relative iron content increased in PD patients compared with HCs (NM-CRHC  = 22.55 ± 1.49; NM-CRPD  = 19.79 ± 1.92; NM-nVolHC  = 2.69 × 10-5  ± 1.02 × 10-5 ; NM-nVolPD  = 1.18 × 10-5  ± 0.96 × 10-5 ; Iron-CRHC  = 10.51 ± 2.64; Iron-CRPD  = 19.35 ± 7.88; Iron-nVolHC  = 0.72 × 10-5  ± 0.81 × 10-5 ; Iron-nVolPD  = 2.82 × 10-5  ± 2.04 × 10-5 ). Binary logistic regression analyses combining N1 and SNc image parameters yielded a top AUC = 0.955. Significant correlation was found between most N1 parameters and both disease duration (ρNM-CR  = -0.31; ρiron-CR  = 0.43; ρiron-nVol  = 0.46) and the motor status (ρNM-nVol  = -0.27; ρiron-CR  = 0.33; ρiron-nVol  = 0.28), suggesting NM reduction along with iron accumulation in N1 as the disease progresses.

DATA CONCLUSION

This method provides a fully automatic N1 segmentation, and the analyses performed reveal that N1 relative NM and iron quantification improves diagnostic performance and suggest a relative NM reduction along with a relative iron accumulation in N1 as the disease progresses.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 1.

Iron homeostasis imbalance and ferroptosis in brain diseases

Brain iron homeostasis is maintained through the normal function of blood-brain barrier and iron regulation at the systemic and cellular levels, which is fundamental to normal brain function. Excess iron can catalyze the generation of free radicals through Fenton reactions due to its dual redox state, thus causing oxidative stress. Numerous evidence has indicated brain diseases, especially stroke and neurodegenerative diseases, are closely related to the mechanism of iron homeostasis imbalance in the brain. For one thing, brain diseases promote brain iron accumulation. For another, iron accumulation amplifies damage to the nervous system and exacerbates patients' outcomes. In addition, iron accumulation triggers ferroptosis, a newly discovered iron-dependent type of programmed cell death, which is closely related to neurodegeneration and has received wide attention in recent years. In this context, we outline the mechanism of a normal brain iron metabolism and focus on the current mechanism of the iron homeostasis imbalance in stroke, Alzheimer's disease, and Parkinson's disease. Meanwhile, we also discuss the mechanism of ferroptosis and simultaneously enumerate the newly discovered drugs for iron chelators and ferroptosis inhibitors.

Locus coeruleus and substantia nigra neuromelanin magnetic resonance imaging differentiates Parkinson's disease and essential tremor

BACKGROUND

Differential diagnosis of essential tremor (ET) and Parkinson's disease (PD) can still be a challenge in clinical practice. These two tremor disorders may have different pathogenesis related to the substantia nigra (SN) and locus coeruleus (LC). Characterizing neuromelanin (NM) in these structures may help improve the differential diagnosis.

METHODS

Forty-three subjects with tremor-dominant PD (PDTD), 31 subjects with ET, and 30 age- and sex-matched healthy controls were included. All subjects were scanned with NM magnetic resonance imaging (NM-MRI). NM volume and contrast measures for the SN and contrast for the LC were evaluated. Logistic regression was used to calculate predicted probabilities by using the combination of SN and LC NM measures. The discriminative power of the NM measures in detecting subjects with PDTD from ET was assessed with a receiver operative characteristic curve, and the area under the curve (AUC) was calculated.

RESULTS

The NM contrast-to-noise ratio (CNR) of the LC, the NM volume, and CNR of the SN on the right and left sides were significantly lower in PDTD subjects than in ET subjects or healthy controls (all P < 0.05). Furthermore, when combining the best model constructed from the NM measures, the AUC reached 0.92 in differentiating PDTD from ET.

CONCLUSION

The NM volume and contrast measures of the SN and contrast for the LC provided a new perspective on the differential diagnosis of PDTD and ET, and the investigation of the underlying pathophysiology.