Neuromelanin magnetic resonance imaging

Neuromelanin magnetic resonance imaging

Neuromelanin-sensitive MRI (NM-MRI) purports to detect the content of neuromelanin (NM), a product of dopamine metabolism that accumulates with age in dopamine neurons of the substantia nigra (SN). Interindividual variability in dopamine function may result in varying levels of NM accumulation in the SN; however, the ability of NM-MRI to measure dopamine function in nonneurodegenerative conditions has not been established.


Neuromelanin sensitive MRI may be the method of choice for the follow-up of meningeal melanocytoma 1).


Cassidy et al. validated that NM-MRI signal intensity in postmortem midbrain specimens correlated with regional NM concentration even in the absence of neurodegeneration, a prerequisite for its use as a proxy for dopamine function. They then validated a voxelwise NM-MRI approach with sufficient anatomical sensitivity to resolve SN subregions. Using this approach and a multimodal dataset of molecular PET and fMRI data, they further showed the NM-MRI signal was related to both dopamine release in the dorsal striatum and resting blood flow within the SN. These results suggest that NM-MRI signal in the SN is a proxy for function of dopamine neurons in the nigrostriatal pathway. As a proof of concept for its clinical utility, we show that the NM-MRI signal correlated to severity of psychosis in schizophrenia and individuals at risk for schizophrenia, consistent with the well-established dysfunction of the nigrostriatal pathway in psychosis. The results indicate that noninvasive NM-MRI is a promising tool that could have diverse research and clinical applications to investigate in vivo the role of dopamine in neuropsychiatric illness 2).


A study aimed to evaluate the accuracy and diagnostic test performance of the U-net-based segmentation method in neuromelanin magnetic resonance imaging (NM-MRI) compared to the established manual segmentation method for Parkinson’s disease diagnosis.

NM-MRI datasets from two different 3T-scanners were used: a “principal dataset” with 122 participants and an “external validation dataset” with 24 participants, including 62 and 12 PD patients, respectively. Two radiologists performed SNpc manual segmentation. Inter-reader precision was determined using Dice coefficients. The U-net was trained with manual segmentation as ground truth and Dice coefficients used to measure accuracy. Training and validation steps were performed on the principal dataset using a 4-fold cross-validation method. We tested the U-net on the external validation dataset. SNpc hyperintense areas were estimated from U-net and manual segmentation masks, replicating a previously validated thresholding method, and their diagnostic test performances for PD determined.

For SNpc segmentation, U-net accuracy was comparable to inter-reader precision in the principal dataset (Dice coefficient: U-net, 0.83 ± 0.04; inter-reader, 0.83 ± 0.04), but lower in external validation dataset (Dice coefficient: U-net, 079 ± 0.04; inter-reader, 0.85 ± 0.03). Diagnostic test performances for PD were comparable between U-net and manual segmentation methods in both principal (area under the receiver operating characteristic curve: U-net, 0.950; manual, 0.948) and external (U-net, 0.944; manual, 0.931) datasets.

U-net segmentation provided relatively high accuracy in the evaluation of the SNpc in NM-MRI and yielded diagnostic performance comparable to that of the established manual method 3)

References

1)

Matsuno H, Takasu S, Seki Y. Usefulness of Neuromelanin Sensitive MRI for En Plaque Meningeal Melanocytoma Involving the Cavernous Sinus: A Case Report. NMC Case Rep J. 2019 Mar 21;6(2):43-46. doi: 10.2176/nmccrj.cr.2018-0211. eCollection 2019 Apr. PubMed PMID: 31016099; PubMed Central PMCID: PMC6476814.
2)

Cassidy CM, Zucca FA, Girgis RR, Baker SC, Weinstein JJ, Sharp ME, Bellei C, Valmadre A, Vanegas N, Kegeles LS, Brucato G, Jung Kang U, Sulzer D, Zecca L, Abi-Dargham A, Horga G. Neuromelanin-sensitive MRI as a noninvasive proxy measure of dopamine function in the human brain. Proc Natl Acad Sci U S A. 2019 Mar 12;116(11):5108-5117. doi: 10.1073/pnas.1807983116. Epub 2019 Feb 22. PubMed PMID: 30796187; PubMed Central PMCID: PMC6421437.
3)

Le Berre A, Kamagata K, Otsuka Y, Andica C, Hatano T, Saccenti L, Ogawa T, Takeshige-Amano H, Wada A, Suzuki M, Hagiwara A, Irie R, Hori M, Oyama G, Shimo Y, Umemura A, Hattori N, Aoki S. Convolutional neural network-based segmentation can help in assessing the substantia nigra in neuromelanin MRI. Neuroradiology. 2019 Aug 10. doi: 10.1007/s00234-019-02279-w. [Epub ahead of print] PubMed PMID: 31401723.

Ferumoxytol magnetic resonance imaging for intracranial arteriovenous malformation

Ferumoxytol magnetic resonance imaging for intracranial arteriovenous malformation

Central nervous system vascular malformations (VMs) result from abnormal vascular- and/or angiogenesis. Cavernomas and arteriovenous malformations are also sites of active inflammation 1).

Inflammation is increasingly being recognized as contributing to the underlying pathophysiology of cerebral aneurysms and brain arteriovenous malformationFerumoxytol is being increasingly used for both its prolonged intravascular imaging characteristics and its utility as an inflammatory marker when imaged in a delayed fashion 2) 3) 4) 5).

Children with intracranial arteriovenous malformations (AVMs) undergo digital DSA for lesion surveillance following their initial diagnosis. However, DSA carries risks of radiation exposure, particularly for the growing pediatric brain and over lifetime. Huang et al. evaluated whether MRI enhanced with a blood pool ferumoxytol (Fe) contrast agent (Fe-MRI) can be used for surveillance of residual or recurrent AVMs.

A retrospective cohort was assembled of children with an established AVM diagnosis who underwent surveillance by both DSA and 3-T Fe-MRI from 2014 to 2016. Two neuroradiologists blinded to the DSA results independently assessed Fe-enhanced T1-weighted spoiled gradient recalled acquisition in steady state (Fe-SPGR) scans and, if available, arterial spin labeling (ASL) perfusion scans for residual or recurrent AVMs. Diagnostic confidence was examined using a Likert scale. Sensitivity, specificity, and intermodality reliability were determined using DSA studies as the gold standard. Radiation exposure related to DSA was calculated as total dose area product (TDAP) and effective dose.

Fifteen patients were included in this study (mean age 10 years, range 3-15 years). The mean time between the first surveillance DSA and Fe-MRI studies was 17 days (SD 47). Intermodality agreement was excellent between Fe-SPGR and DSA (κ = 1.00) but poor between ASL and DSA (κ = 0.53; 95% CI 0.18-0.89). The sensitivity and specificity for detecting residual AVMs using Fe-SPGR were 100% and 100%, and using ASL they were 72% and 100%, respectively. Radiologists reported overall high diagnostic confidence using Fe-SPGR. On average, patients received two surveillance DSA studies over the study period, which on average equated to a TDAP of 117.2 Gy×cm2 (95% CI 77.2-157.4 Gy×cm2) and an effective dose of 7.8 mSv (95% CI 4.4-8.8 mSv).

Fe-MRI performed similarly to DSA for the surveillance of residual AVMs. Future multicenter studies could further investigate the efficacy of Fe-MRI as a noninvasive alternative to DSA for monitoring AVMs in children 6).


The purpose of a study was to evaluate the performance of ferumoxytol-enhanced MRA using a high-resolution 3D volumetric sequence (fe-SPGR) for visualizing and grading pediatric brain AVMs in comparison with CTA and DSA, which is the current imaging gold standard. METHODS In this retrospective cohort study, 21 patients with AVMs evaluated by fe-SPGR, CTA, and DSA between April 2014 and August 2017 were included. Two experienced raters graded AVMs using Spetzler-Martin criteria on all imaging studies. Lesion conspicuity (LC) and diagnostic confidence (DC) were assessed using a 5-point Likert scale, and interrater agreement was determined. The Kruskal-Wallis test was performed to assess the raters’ grades and scores of LC and DC, with subsequent post hoc pairwise comparisons to assess for statistically significant differences between pairs of groups at p < 0.05. RESULTS Assigned Spetzler-Martin grades for AVMs on DSA, fe-SPGR, and CTA were not significantly different (p = 0.991). LC and DC scores were higher with fe-SPGR than with CTA (p < 0.05). A significant difference in LC scores was found between CTA and fe-SPGR (p < 0.001) and CTA and DSA (p < 0.001) but not between fe-SPGR and DSA (p = 0.146). A significant difference in DC scores was found among DSA, fe-SPGR, and CTA (p < 0.001) and between all pairs of the groups (p < 0.05). Interrater agreement was good to very good for all image groups (κ = 0.77-1.0, p < 0.001). CONCLUSIONS Fe-SPGR performed robustly in the diagnostic evaluation of brain AVMs, with improved visual depiction of AVMs compared with CTA and comparable Spetzler-Martin grading relative to CTA and DSA 7).

References

1)

Dósa E, Tuladhar S, Muldoon LL, Hamilton BE, Rooney WD, Neuwelt EA. MRI using ferumoxytol improves the visualization of central nervous system vascular malformations. Stroke. 2011 Jun;42(6):1581-8. doi: 10.1161/STROKEAHA.110.607994. Epub 2011 Apr 14. PubMed PMID: 21493906; PubMed Central PMCID: PMC3412426.
2)

Zanaty M, Chalouhi N, Starke RM, Jabbour P, Hasan D. Molecular Imaging in Neurovascular Diseases: The Use of Ferumoxytol to Assess Cerebral Aneurysms and Arteriovenous Malformations. Top Magn Reson Imaging. 2016 Apr;25(2):57-61. doi: 10.1097/RMR.0000000000000086. Review. PubMed PMID: 27049242.
3)

Chalouhi N, Jabbour P, Magnotta V, Hasan D. Molecular imaging of cerebrovascular lesions. Transl Stroke Res. 2014 Apr;5(2):260-8. doi: 10.1007/s12975-013-0291-0. Epub 2013 Oct 23. Review. PubMed PMID: 24323714.
4)

Chalouhi N, Jabbour P, Magnotta V, Hasan D. The emerging role of ferumoxytol-enhanced MRI in the management of cerebrovascular lesions. Molecules. 2013 Aug 13;18(8):9670-83. doi: 10.3390/molecules18089670. Review. PubMed PMID: 23945642; PubMed Central PMCID: PMC6270297.
5)

Hasan DM, Amans M, Tihan T, Hess C, Guo Y, Cha S, Su H, Martin AJ, Lawton MT, Neuwelt EA, Saloner DA, Young WL. Ferumoxytol-enhanced MRI to Image Inflammation within Human Brain Arteriovenous Malformations: A Pilot Investigation. Transl Stroke Res. 2012 Jul;3(Suppl 1):166-73. doi: 10.1007/s12975-012-0172-y. PubMed PMID: 23002401; PubMed Central PMCID: PMC3445332.
6)

Huang Y, Singer TG, Iv M, Lanzman B, Nair S, Stadler JA, Wang J, Edwards MSB, Grant GA, Cheshier SH, Yeom KW. Ferumoxytol-enhanced MRI for surveillance of pediatric cerebral arteriovenous malformations. J Neurosurg Pediatr. 2019 Jul 19:1-8. doi: 10.3171/2019.5.PEDS1957. [Epub ahead of print] PubMed PMID: 31323627.
7)

Iv M, Choudhri O, Dodd RL, Vasanawala SS, Alley MT, Moseley M, Holdsworth SJ, Grant G, Cheshier S, Yeom KW. High-resolution 3D volumetric contrast-enhanced MR angiography with a blood pool agent (ferumoxytol) for diagnostic evaluation of pediatric brain arteriovenous malformations. J Neurosurg Pediatr. 2018 Sep;22(3):251-260. doi: 10.3171/2018.3.PEDS17723. Epub 2018 Jun 8. PubMed PMID: 29882734.

Diffusion tensor imaging for trigeminal neuralgia

Diffusion tensor imaging for trigeminal neuralgia

Trigeminal neuralgia (TN) is often classified as type 1 (TN1) when pain is primarily paroxysmal and episodic or type 2 (TN2) when pain is primarily constant in character. Diffusion tensor imaging (DTI) has revealed microstructural changes in the symptomatic trigeminal root and root entry zone of patients with unilateral TN.

Noninvasive DTI analysis of patients with TN may lead to improved trigeminal neuralgia diagnosis of TN subtypes (e.g., TN1 and TN2) and improve patient selection for surgical intervention. DTI measurements may also provide insights into prognosis after intervention, as TN1 patients are known to have better surgical outcomes than TN2 patients 1).


As diffusion tensor imaging (DTI) is able to assess tissue integrity, Leal et al., used diffusion to detect abnormalities in trigeminal nerves (TGN) in patients with trigeminal neuralgia (TN) caused by neurovascular compression (NVC) who had undergone microvascular decompression (MVD).

Using DTI sequencing on a 3-T MRI scanner, we measured the fraction of anisotropy (FA) and apparent diffusion coefficient (ADC) of the TGN in 10 patients who had undergone MVD for TN and in 6 normal subjects. We compared data between affected and unaffected nerves in patients and both nerves in normal subjects (controls). We then correlated these data with CSA and V. Data from the affected side and the unaffected side before and 4 years after MVD were compared.

RESULTS: Before MVD, the FA of the affected side (0.37 ± 0.03) was significantly lower (p < 0.05) compared to the unaffected side in patients (0.48 ± 0.03) and controls (0.52 ± 0.02), and the ADC in the affected side (5.6 ± 0.34 mm2/s) was significantly higher (p < 0.05) compared to the unaffected side in patients (4.26 ± 0.25 mm2/s) and controls (3.84 ± 0.18 mm2/s). Affected nerves had smaller V and CSA compared to unaffected nerves and controls (p < 0.05). After MVD, the FA in the affected side (0.41 ± 0.02) remained significantly lower (p < 0.05) compared to the unaffected side (0.51 ± 0.02), but the ADC in the affected side (4.24 ± 0.34 mm2/s) had become similar (p > 0.05) to the unaffected side (4.01 ± 0.33 mm2/s).

CONCLUSIONS: DTI revealed a loss of anisotropy and an increase in diffusivity in affected nerves before surgery. Diffusion alterations correlated with atrophic changes in patients with TN caused by NVC. After removal of the compression, the loss of FA remained, but ADC normalized in the affected nerves, suggesting improvement in the diffusion of the trigeminal root 2).


Herveh et al. studied the trigeminal nerve in seven healthy volunteers and six patients with trigeminal neuralgia using the diffusion tensor imagingderived parameter fractional anisotropy (FA). While controls did not show a difference between both sides, there was a reduction of FA in the affected nerve in three of six patients with accompanying nerve-vessel conflict and atrophy. Reversibility of abnormally low FA values was demonstrated in one patient successfully treated with microvascular decompression 3).


3T MR diffusion weighted, T1, T2 and FLAIR sequences were acquired for Multiple sclerosis related trigeminal neuralgia MS-TN, TN, and controls. Multi-tensor tractography was used to delineate CN V across cisternal, root entry zone (REZ), pontine and peri-lesional segments. Diffusion metrics including fractional anisotropy (FA), and radial (RD), axial (AD), and mean diffusivities (MD) were measured from each segment.

CN V segments showed distinctive diffusivity patterns. The TN group showed higher FA in the cisternal segment ipsilateral to the side of pain, and lower FA in the ipsilateral REZ segment. The MS-TN group showed lower FA in the ipsilateral peri-lesional segments, suggesting differential microstructural changes along CN V in these conditions.

The study demonstrates objective differences in CN V microstrucuture in TN and MS-TN using non-invasive neuroimaging. This represents a significant improvement in the methods currently available to study pain in MS 4).


The aim of a study was to evaluate the microstructural tissue abnormalities in the trigeminal nerve in symptomatic trigeminal neuralgia not related to neurovascular compression using diffusion tensor imaging. Mean values of the quantitative diffusion parameters of trigeminal nerve, fractional anisotropy and apparent diffusion coefficient, were measured in a group of four symptomatic trigeminal neuralgia patients without neurovascular compression who showed focal non-enhancing T2-hyperintense lesions in the pontine trigeminal pathway. These diffusion parameters were compared between the affected and unaffected sides in the same patient and with four age-matched healthy controls. Cranial magnetic resonance imaging revealed hyperintense lesions in the dorsolateral part of the pons along the central trigeminal pathway on T2-fluid-attenuated inversion recovery sequences. The mean fractional anisotropy value on the affected side was significantly decreased (P = 0.001) compared to the unaffected side and healthy controls. Similarly, the mean apparent diffusion coefficient value was significantly higher (P = 0.001) on the affected side compared to the unaffected side and healthy controls. The cause of trigeminal neuralgia in our patients was abnormal pontine lesions affecting the central trigeminal pathway. The diffusion tensor imaging results suggest that microstructural tissue abnormalities of the trigeminal nerve also exist even in non-neurovascular compression-related trigeminal neuralgia 5).


DTI analysis allows the quantification of structural alterations, even in those patients without any discernible neurovascular contact on MRI. Moreover, our findings support the hypothesis that both the arteries and veins can cause structural alterations that lead to TN. These aspects can be useful for making treatment decisions 6).


The mean diameter of compression arteries (DCA) in NVC patients with TN (1.58 ± 0.34 mm) was larger than that without TN (0.89 ± 0.29 mm). Compared with NVC without TN and HC, the mean values of RD at the site of NVC with TN were significantly increased; however, no significant changes of AD were found between the groups. Correlation analysis showed that DCA positively correlated with radial diffusivity (RD) in NVC patients with and without TN (r = 0.830, p = 0.000). No significant correlation was found between DCA and axial diffusivity (AD) (r = 0.178, p = 0.077).

Larger-diameter compression arteries may increase the chances of TN, and may be a possible facilitating factor for TN 7).


Fractional anisotropy (FA) value quantitatively showed the alteration of trigeminal nerve (TGN) caused by Neurovascular compression (NVC). It provided direct evidence about the effect of NVC which facilitated the diagnosis and surgical decision of Type 2 trigeminal neuralgia (TN) . Besides, significant reduction of FA value may predict an optimistic outcome of microvascular decompression (MVD) 8).


Sophisticated structural MRI techniques including diffusion tensor imaging provide new opportunities to assess the trigeminal nerves and CNS to provide insight into TN etiology and pathogenesis. Specifically, studies have used high-resolution structural MRI methods to visualize patterns of trigeminal nerve-vessel relationships and to detect subtle pathological features at the trigeminal REZ. Structural MRI has also identified CNS abnormalities in cortical and subcortical gray matter and white matter and demonstrated that effective neurosurgical treatment for TN is associated with a reversal of specific nerve and brain abnormalities 9).


Forty-three patients with trigeminal neuralgia were recruited, and diffusion tensor imaging was performed before radiofrequency rhizotomy. By selecting the cisternal segment of the trigeminal nerve manually, they measured the volume of trigeminal nerve, fractional anisotropy, apparent diffusion coefficient, axial diffusivity, and radial diffusivity. The apparent diffusion coefficient and mean value of fractional anisotropy, axial diffusivity, and radial diffusivity were compared between the affected and normal side in the same patient, and were correlated with pre-rhizotomy and post-rhizotomy visual analogue scale pain scores. The results showed the affected side had significantly decreased fractional anisotropy, increased apparent diffusion coefficient and radial diffusivity, and no significant change of axial diffusivity. The volume of the trigeminal nerve on affected side was also significantly smaller. There was a trend of fractional anisotropy reduction and visual analogue scale pain score reduction (P = 0.072). The results suggest that demyelination without axonal injury, and decreased size of the trigeminal nerve, are the microstructural abnormalities of the trigeminal nerve in patients with trigeminal neuralgia caused by neurovascular compression. The application of diffusion tensor imaging in understanding the pathophysiology of trigeminal neuralgia, and predicting the treatment effect has potential and warrants further study 10).

References

1)

Willsey MS, Collins KL, Conrad EC, Chubb HA, Patil PG. Diffusion tensor imaging reveals microstructural differences between subtypes of trigeminal neuralgia. J Neurosurg. 2019 Jul 19:1-7. doi: 10.3171/2019.4.JNS19299. [Epub ahead of print] PubMed PMID: 31323635.
2)

Leal PRL, Roch J, Hermier M, Berthezene Y, Sindou M. Diffusion tensor imaging abnormalities of the trigeminal nerve root in patients with classical trigeminal neuralgia: a pre- and postoperative comparative study 4 years after microvascular decompression. Acta Neurochir (Wien). 2019 May 2. doi: 10.1007/s00701-019-03913-5. [Epub ahead of print] PubMed PMID: 31049710.
3)

Herweh C, Kress B, Rasche D, Tronnier V, Tröger J, Sartor K, Stippich C. Loss of anisotropy in trigeminal neuralgia revealed by diffusion tensor imaging. Neurology. 2007 Mar 6;68(10):776-8. PubMed PMID: 17339587.
4)

Chen DQ, DeSouza DD, Hayes DJ, Davis KD, O’Connor P, Hodaie M. Diffusivity signatures characterize trigeminal neuralgia associated with multiple sclerosis. Mult Scler. 2016 Jan;22(1):51-63. doi: 10.1177/1352458515579440. PubMed PMID: 25921052.
5)

Neetu S, Sunil K, Ashish A, Jayantee K, Usha Kant M. Microstructural abnormalities of the trigeminal nerve by diffusion-tensor imaging in trigeminal neuralgia without neurovascular compression. Neuroradiol J. 2016 Feb;29(1):13-8. doi: 10.1177/1971400915620439. PubMed PMID: 26678753; PubMed Central PMCID: PMC4978338.
6)

Lutz J, Thon N, Stahl R, Lummel N, Tonn JC, Linn J, Mehrkens JH. Microstructural alterations in trigeminal neuralgia determined by diffusion tensor imaging are independent of symptom duration, severity, and type of neurovascular conflict. J Neurosurg. 2016 Mar;124(3):823-30. doi: 10.3171/2015.2.JNS142587. PubMed PMID: 26406792.
7)

Lin W, Zhu WP, Chen YL, Han GC, Rong Y, Zhou YR, Zhang QW. Large-diameter compression arteries as a possible facilitating factor for trigeminal neuralgia: analysis of axial and radial diffusivity. Acta Neurochir (Wien). 2016 Mar;158(3):521-6. doi: 10.1007/s00701-015-2673-4. PubMed PMID: 26733127; PubMed Central PMCID: PMC4752583.
8)

Chen F, Chen L, Li W, Li L, Xu X, Li W, Le W, Xie W, He H, Li P. Pre-operative declining proportion of fractional anisotropy of trigeminal nerve is correlated with the outcome of micro-vascular decompression surgery. BMC Neurol. 2016 Jul 16;16:106. doi: 10.1186/s12883-016-0620-5. PubMed PMID: 27422267; PubMed Central PMCID: PMC4947245.
9)

DeSouza DD, Hodaie M, Davis KD. Structural Magnetic Resonance Imaging Can Identify Trigeminal System Abnormalities in Classical Trigeminal Neuralgia. Front Neuroanat. 2016 Oct 19;10:95. Review. PubMed PMID: 27807409; PubMed Central PMCID: PMC5070392.
10)

Chen ST, Yang JT, Yeh MY, Weng HH, Chen CF, Tsai YH. Using Diffusion Tensor Imaging to Evaluate Microstructural Changes and Outcomes after Radiofrequency Rhizotomy of Trigeminal Nerves in Patients with Trigeminal Neuralgia. PLoS One. 2016 Dec 20;11(12):e0167584. doi: 10.1371/journal.pone.0167584. PubMed PMID: 27997548.
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