Diffusion tensor imaging for degenerative cervical myelopathy

Diffusion tensor imaging for degenerative cervical myelopathy

Despite its invasiveness, computed tomography myelography (CTM) is still considered an important supplement to conventional magnetic resonance imaging (MRI) for preoperative evaluation of multilevel degenerative cervical myelopathy. Schöller et al., analyzed if diffusion tensor imaging (DTI) could be a less invasive alternative for this purpose.

In 20 patients with degenerative cervical myelopathy and an indication for decompression of at least one level, CTM was performed preoperatively to determine the extent of spinal canal/cerebrospinal fluid (CSF) space and cord compression (Naganawa score) for a decision on the number of levels to be decompressed. Fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were correlated with these parameters and with MRI-based increased signal intensity (ISI). Receiver operating characteristic analysis was performed to determine the sensitivity to discriminate levels requiring decompression surgery. European Myelopathy Score(EMS) and neck/radicular visual analog scale (VAS-N/R) were used for clinical evaluation.

According to preoperative CTM, 20 levels of maximum and 16 levels of relevant additional stenosis were defined and decompressed. Preoperative FA and particularly ADC showed a significant correlation with the CTM Naganawa score but also with the ISI grade. Furthermore, both FA and ADC facilitated a good discrimination between stenotic and nonstenotic levels with cutoff values < 0.49 for FA and > 1.15 × 10-9 m2/s for ADC. FA and especially ADC revealed a considerably higher sensitivity (79% and 82%, respectively) in discriminating levels requiring decompression surgery compared with ISI (55%). EMS and VAS-N/R were significantly improved at 14 months compared with preoperative values.

DTI parameters are highly sensitive at distinguishing surgical from nonsurgical levels in CSM patients and might therefore represent a less invasive alternative to CTM for surgical planning 1).


A study population included 50 patients with symptoms of cervical myelopathy. The patients were evaluated based on symptoms using the European myelopathy scoring system and were divided into: Grade 1, including patients with mild symptoms; Grade 2, referring to patients with moderate symptoms and Grade 3, which included patients revealing severe symptoms. All the patients were investigated with a 1.5 T MRI unit acquiring DWI and DTI sequences. FA and ADC values from each spinal segment were analyzed in terms of Frequency, Percentage, Mean, Standard Deviation and Confidence Intervals. The comparison of values was done by ANOVA and post hoc analysis by bonferroni test. Comparison of accuracy of FA, ADC and T2WI in recognizing myelopathic changes was done by t-test. Receiver Operating Characteristics (ROC) analysis was performed to obtain a cut off value of FA and ADC for each spinal level to identify myelopathic change in the spinal cord.

The study revealed a significant difference in the mean FA and ADC value of stenotic and Non-stenotic segments. T2WI was highly significant (p = 0.000) in recognizing myelopathy changes in patients falling under Grade 2(moderate) and Grade 3(severe) according to European Myelopathy scoring system. Regarding patients under Grade 1 (mild) FA and ADC values showed significant difference compared to T2WI. The collective sensitivity in the identification of myelopathic changes was highest with FA (79%) as compared to ADC (71%) and T2WI (50%). ROC analysis was done to determine the cut off values of FA and ADC at each cervical spine segments. The proposed cut off, for FA and ADC at the level of C1-C2 is 0.68 and 0.92, C2-C3 is 0.65 and 1.03, C3-C4 is 0.63 and 1.01, C4-C5 0.61 and 0.98, At C5-C6 0.57 and 1.04, At C6-C7 0.56 and 0.96 respectively.

FA and ADC values enhance the efficacy and accuracy of MRI in the diagnosis of cervical spondylotic myelopathy. Hence diffusion tensor imaging can be used as a non-invasive modality to recognize spondylotic myelopathy changes even in the early stages, which can be helpful in deciding on appropriate timing of decompression surgery before the irreversible chronic changes set in 2).


A meta-analysis was conducted to assess alterations in measures of diffusion tensor imaging (DTI) in the patients of cervical spondylotic myelopathy (CSM), exploring the potential role of DTI as a diagnosis biomarker. A systematic search of all related studies written in English was conducted using PubMed, Web of Science, EMBASE, CINAHL, and Cochrane comparing CSM patients with healthy controls. Key details for each study regarding participants, imaging techniques, and results were extracted. DTI measurements, such as fractional anisotropy (FA), apparent diffusion coefficient (ADC), and mean diffusivity (MD) were pooled to calculate the effect size (ES) by fixed or random effects meta-analysis. 14 studies involving 479 CSM patients and 278 controls were identified. Meta-analysis of the most compressed levels (MCL) of CSM patients demonstrated that FA was significantly reduced (ES -1.52, 95% CI -1.87 to -1.16, P < 0.001) and ADC was significantly increased (ES 1.09, 95% CI 0.89 to 1.28, P < 0.001). In addition, a notable ES was found for lowered FA at C2-C3 for CSM vs. controls (ES -0.83, 95% CI -1.09 to -0.570, P < 0.001). Meta-regression analysis revealed that male ratio of CSM patients had a significant effect on reduction of FA at MCL (P = 0.03). The meta-analysis of DTI studies of CSM patients clearly demonstrated a significant FA reduction and ADC increase compared with healthy subjects. This result supports the use of DTI parameters in differentiating CSM patients from health subjects. Future researches are required to investigate the diagnosis performance of DTI in cervical spondylotic myelopathy 3).


The measurement of DTI indexes within the spinal cord provides a quantitative assessment of neural damage in various spinal cord pathologies. DTI studies in animal models of spinal cord injury indicate that DTI is a reliable imaging technique with important histological and functional correlates.

DTI is a noninvasive marker of microstructural change within the spinal cord. In human studies, spinal cord DTI shows definite changes in subjects with acute and chronic spinal cord injury, as well as cervical spondylotic myelopathy. Interestingly, changes in DTI indexes are visualized in regions of the cord, which appear normal on conventional magnetic resonance imaging and are remote from the site of cord compression. Spinal cord DTI provides data that can help us understand underlying microstructural changes within the cord and assist in prognostication and planning of therapies 4).

References

1)

Schöller K, Siller S, Brem C, Lutz J, Zausinger S. Diffusion Tensor Imaging for Surgical Planning in Patients with Cervical Spondylotic Myelopathy. J Neurol Surg A Cent Eur Neurosurg. 2019 Jun 10. doi: 10.1055/s-0039-1691822. [Epub ahead of print] PubMed PMID: 31181580.
2)

Nukala M, Abraham J, Khandige G, Shetty BK, Rao APA. Efficacy of diffusion tensor imaging in identification of degenerative cervical spondylotic myelopathy. Eur J Radiol Open. 2018 Dec 12;6:16-23. doi: 10.1016/j.ejro.2018.08.006. eCollection 2019. PubMed PMID: 30581892; PubMed Central PMCID: PMC6293016.
3)

Guan X, Fan G, Wu X, Gu G, Gu X, Zhang H, He S. Diffusion tensor imaging studies of cervical spondylotic myelopathy: a systemic review and meta-analysis. PLoS One. 2015 Feb 11;10(2):e0117707. doi: 10.1371/journal.pone.0117707. eCollection 2015. Review. PubMed PMID: 25671624; PubMed Central PMCID: PMC4363894.
4)

Vedantam A, Jirjis MB, Schmit BD, Wang MC, Ulmer JL, Kurpad SN. Diffusion tensor imaging of the spinal cord: insights from animal and human studies. Neurosurgery. 2014 Jan;74(1):1-8. doi: 10.1227/NEU.0000000000000171. PubMed PMID: 24064483.

Susceptibility weighted imaging for glioma

Susceptibility weighted imaging for glioma

Gradient echo T2WI MRI is the 3–4 × more sensitive test than FLAIR for demonstrating intraparenchymablood (which appears dark) due to high sensitivity to paramagnetic artifact. It is not as sensitive as SWI.

Susceptibility weighted imaging (SWI) of brain tumors provides information about neoplastic vasculature and intratumoral micro- and macrobleedings. Low- and high-grade gliomas can be distinguished by SWI due to their different vascular characteristics. Fractal analysis allows for quantification of these radiological differences by a computer-based morphological assessment of SWI patterns.

SWI and CE-SWI are indispensable tools for diagnosis, preoperative grading, posttherapy surveillance, and assessment of glioma 1).

The theory that susceptibility signals show microvasculature that correlates with tumor grade has been well validated with the help of various studies. However, the cons of SWI lie within the technique itself. Small tweaks made in imaging parameters lead to varying subjective results. This lack of standardization of the SWI technique remains an obstacle in its integration into mainstream grading of gliomas. SWI for now plays an important role in detecting gliomas and guiding biopsies. The goal of noninvasive accurate grading of tumors is yet to be realized. Further studies with greater sample size and better collaborations are warranted in this regard 2).


Eighteen GBM patients were retrospectively analyzed. After completion of therapy, imaging was performed every 3 months. MRI was analyzed at the following time points: after the third and sixth cycle of adjuvant temozolomide chemotherapy, thereafter in 3 month intervals and at recurrence. The number of SWI positive tumor pixels was quantified and compared with progression as defined by the RANO criteria on T2- and contrast-enhanced T1-weighted MRI sequences (T1-CE).

The MRI interval between completion of the sixth chemotherapy cycle and last MRI before progression was 390 ± 292 days. Between the last MRI before progression and at progression a significant increase in SWI positive tumor pixels was observed (P = .012), whereas tumor size remained unchanged (RANO T2: P = .385; RANO T1-CE: P = .165). The number of SWI positive pixels remained unchanged between last MRI before progression until progression (P = .149), whereas RANO T2 and T1-CE showed tumor progression (interval 128 ± 69 days).

SWI positive pixel count increases significantly prior to changes in tumor size (RANO). The findings may be explained by microbleeds compatible with stimulation of angiogenesis and possibly serve as an early biomarker of tumor progression 3).


Seventy-eight patients affected by brain tumors of different histopathology (low- and high-grade gliomas, metastases, meningiomas, lymphomas) were included. All patients underwent preoperative 3-T magnetic resonance imaging including SWI, on which the lesions were contoured. The images underwent automated computation, extracting 2 quantitative parameters: the volume fraction of SWI signals within the tumors (signal ratio) and the morphological self-similar features (fractal dimension [FD]). The results were then correlated with each histopathological type of tumor.

Signal ratio and FD were able to differentiate low-grade gliomas from grade III and IV gliomas, metastases, and meningiomas (P < .05). FD was statistically different between lymphomas and high-grade gliomas (P < .05). A receiver-operating characteristic analysis showed that the optimal cutoff value for differentiating low- from high-grade gliomas was 1.75 for FD (sensitivity, 81%; specificity, 89%) and 0.03 for signal ratio (sensitivity, 80%; specificity, 86%).

FD of SWI on 3-T magnetic resonance imaging is a novel image biomarker for glioma grading and brain tumor characterization. Computational models offer promising results that may improve diagnosis and open perspectives in the radiological assessment of brain tumors 4).

References

1)

Hsu CC, Watkins TW, Kwan GN, Haacke EM. Susceptibility-Weighted Imaging of Glioma: Update on Current Imaging Status and Future Directions. J Neuroimaging. 2016 Jul;26(4):383-90. doi: 10.1111/jon.12360. Epub 2016 May 26. Review. PubMed PMID: 27227542.
2)

Mohammed W, Xunning H, Haibin S, Jingzhi M. Clinical applications of susceptibility-weighted imaging in detecting and grading intracranial gliomas: a review. Cancer Imaging. 2013 Apr 24;13:186-95. doi: 10.1102/1470-7330.2013.0020. Review. PubMed PMID: 23618919; PubMed Central PMCID: PMC3636597.
3)

van Leyen K, Roelcke U, Gruber P, Remonda L, Berberat J. Susceptibility and Tumor Size Changes During the Time Course of Standard Treatment in Recurrent Glioblastoma. J Neuroimaging. 2019 May 21. doi: 10.1111/jon.12631. [Epub ahead of print] PubMed PMID: 31112344.
4)

Di Ieva A, Le Reste PJ, Carsin-Nicol B, Ferre JC, Cusimano MD. Diagnostic Value of Fractal Analysis for the Differentiation of Brain Tumors Using 3-Tesla Magnetic Resonance Susceptibility-Weighted Imaging. Neurosurgery. 2016 Dec;79(6):839-846. PubMed PMID: 27332779.

Magnetic resonance perfusion imaging in glioblastoma

Indications

Magnetic resonance perfusion imaging, may:

Provide a noninvasive diagnostic tool for properly grading lesions.

Identifying the most malignant region of a tumor for guiding biopsy

Monitoring response to therapy that may precede conventionally assessed changes in tumor morphology and enhancement characteristics.

May help quantitatively predict recurrent glioblastoma/progression for glioblastomas. The active tumor histological fraction correlated with quantitative radiologic measurements including rCBV and rCBF.

The dominant predictors of OS are normalized perfusion parameters Normalized Relative Tumor Blood Volume (n_rTBV) and Normalized Relative Tumor Blood Flow (n_rTBF). Pre-operative perfusion imaging may be used as a surrogate to predict glioblastoma aggressiveness and survival independent of treatment 1).


For metastases, Perfusion MRI may not be as useful in predicting mean active tumor fraction (AT). Clinicians must be judicious with their use of MRP in predicting tumor recurrence and radiation necrosis 2).

While perfusion MRI is not the ideal diagnostic method for differentiating glioma recurrence from pseudoprogression, it could improve diagnostic accuracy. Therefore, further research on combining perfusion MRI with other imaging modalities is warranted 3).

Perfusion-weighted magnetic resonance imaging (PW-MRI) techniques, such as dynamic contrast-enhanced MRI (DCE-MRI) and dynamic susceptibility contrast-MRI (DSC-MRI), have demonstrated much potential as powerful imaging biomarkers for glioma management as they can provide information of vascular hemodynamics 4) 5) 6).

PW-MRI is now rapidly expanding its application spectrum by noninvasively exploring the relationship between imaging parameters and the molecular characteristics of gliomas 7).


Dynamic contrast enhanced magnetic resonance imaging and Dynamic susceptibility weighted contrast enhanced perfusion imaging represent a widely accepted method to assess glioblastoma (GBM) microvasculature.

The aim of Navone et al. from the Laboratory of Experimental Neurosurgery and Cell Therapy, Neurosurgery Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Postgraduate School in Radiodiagnostics Department of Neuroradiology, Milan, was to investigate the correlation between plasma von Willebrand Factor (VWF):Ag, permeability and perfusion MRI parameters, and examine their potential in predicting GBM patient prognosis.

They retrospectively analysed pre-operative DCE-, DSC-MRI, and VWF:Ag level of 26 GBM patients. They assessed the maximum values of relative cerebral blood flow (rCBF) and volume (rCBV), volume transfer constant Ktrans, plasma volume (Vp) and reflux rate constant between fractional volume of the extravascular space and blood plasma (Kep). Non-parametric Mann-Withney test and Kaplan-Meier survival analyses were conducted and a p-value<0.05 was considered statistically significant.

The median VWF:Ag value was 248 IU/dL and the median follow-up duration was about 13 months. They divided patients according to low- and high-VWF:Ag and found significant differences in the median follow-up duration (19 months vs 10 months, p=0.04) and in Ktrans (0.31 min-1 vs 0.53 min-1, p=0.02), and Kep (1.79 min-1 vs 3.89 min-1, p=0.005) values. The cumulative 1-year survival was significantly shorter in patients with high-VWF:Ag and high-Kep compared to patients with low-VWF:Ag and low-Kep (37.5% vs. 68%, p = 0.05).

These findings, in a small group of patients, suggest a role for VWF:Ag, similar to Ktrans, and Kep as a prognostic indicator of postoperative GBM patient survival 8).

References

1)

Hou BL, Wen S, Katsevman GA, Liu H, Urhie O, Turner RC, Carpenter J, Bhatia S. MRI Parameters and Their Impact on the Survival of Patients with Glioblastoma: Tumor Perfusion Predicts Survival. World Neurosurg. 2018 Dec 26. pii: S1878-8750(18)32908-5. doi: 10.1016/j.wneu.2018.12.085. [Epub ahead of print] PubMed PMID: 30593971.
2)

Shah AH, Kuchakulla M, Ibrahim GM, Dadheech E, Komotar RJ, Gultekin SH, Ivan ME. The utility of Magnetic Resonance Perfusion imaging in quantifying active tumor fraction and radiation necrosis in recurrent intracranial tumors. World Neurosurg. 2018 Oct 9. pii: S1878-8750(18)32288-5. doi: 10.1016/j.wneu.2018.09.233. [Epub ahead of print] PubMed PMID: 30312826.
3)

Wan B, Wang S, Tu M, Wu B, Han P, Xu H. The diagnostic performance of perfusion MRI for differentiating glioma recurrence from pseudoprogression: A meta-analysis. Medicine (Baltimore). 2017 Mar;96(11):e6333. doi: 10.1097/MD.0000000000006333. PubMed PMID: 28296759; PubMed Central PMCID: PMC5369914.
4)

Jain R. Measurements of tumor vascular leakiness using DCE in brain tumors: clinical applications. NMR in Biomedicine. 2013;26(8):1042–1049. doi: 10.1002/nbm.2994.
5)

O’Connor J. P. B., Jackson A., Parker G. J. M., Roberts C., Jayson G. C. Dynamic contrast-enhanced MRI in clinical trials of antivascular therapies. Nature Reviews Clinical Oncology. 2012;9(3):167–177. doi: 10.1038/nrclinonc.2012.2.
6)

Barajas R. F. R., Cha S. Benefits of dynamic susceptibility-weighted contrast-enhanced perfusion MRI for glioma diagnosis and therapy. CNS oncology. 2014;3(6):407–419. doi: 10.2217/cns.14.44.
7)

Chung C., Metser U., Ménard C. Advances in magnetic resonance imaging and positron emission tomography imaging for grading and molecular characterization of glioma. Seminars in Radiation Oncology. 2015;25(3):164–171. doi: 10.1016/j.semradonc.2015.02.002.
8)

Navone SE, Doniselli FM, Summers P, Guarnaccia L, Rampini P, Locatelli M, Campanella R, Marfia G, Costa A. Correlation of preoperative Von Willebrand Factor with MRI perfusion and permeability parameters as predictors of prognosis in glioblastoma. World Neurosurg. 2018 Oct 9. pii: S1878-8750(18)32271-X. doi: 10.1016/j.wneu.2018.09.216. [Epub ahead of print] PubMed PMID: 30312827.
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