magnetic resonance neurography visualizes abnormalities in ... · 9 schwann cells (2), axonal...

Magnetic Resonance Neurography visualizes abnormalities in sciatic and 1

tibial nerves in patients with type 1 diabetes and neuropathy 2

3

Michael Vaeggemose1,2

, Mirko Pham3, Steffen Ringgaard

4, Hatice Tankisi

5, Niels Ejskjaer

6, 4

Sabine Heiland7, Per L. Poulsen

8, Henning Andersen

1,9 5

6 1Department of Neurology, Aarhus University Hospital, Denmark 7

2Danish Diabetes Academy, Odense, Denmark 8

3Department of Neuroradiology, Würzburg University Hospital, Germany 9

4MR Research Centre, Aarhus University Hospital, Denmark 10

5Department of Clinical Neurophysiology, Aarhus University Hospital, Denmark 11

6Departments of Clinical Medicine and Endocrinology, Aalborg University Hospital, Aalborg 12

7Department of Neuroradiology, Heidelberg University Hospital, Germany 13

8Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Denmark 14

9International Diabetic Neuropathy Consortium (IDNC), Aarhus University, Denmark 15

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17

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Running title: DTI for detection of neuropathy in type 1 diabetes 20

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Word count abstract: 200 26

Word count paper: 3999 27

Number of tables: 4 28

Number of figures: 4 29

Number of references: 48 30

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Correspondence: 38

Michael Vaeggemose 39

Department of Neurology 40

Aarhus University Hospital 41

Noerrebrogade 44 42

DK-8000 Aarhus C 43

Phone: (+45) 7846 3447 44

E-mail: [email protected] 45

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Diabetes Publish Ahead of Print, published online April 21, 2017

Abstract 1

This study evaluates whether diffusion-tensor-imaging MR-Neurography (DTI-MRN), T2-2

relaxation-time and proton-spin-density can detect and grade neuropathic abnormalities in 3

patients with type 1 diabetes. 4

Forty-nine patients with type 1 diabetes (11 with severe polyneuropathy (sDPN), 13 with 5

mild polyneuropathy (mDPN) and 25 without polyneuropathy (nDPN)) and 30 healthy 6

controls (HC) were included. Clinical examinations, nerve-conduction-studies and vibratory-7

perception-thresholds determined the presence and severity of DPN. DTI-MRN covered 8

proximal (sciatic nerve) and distal (tibial nerve) nerve segments of the lower extremity. 9

Fractional-anisotropy (FA) and the apparent-diffusion-coefficient (ADC) were calculated 10

together with T2-relaxation-time and proton-spin-density obtained from DTI-MRN: All MR 11

findings were related to presence and severity of neuropathy. 12

FA of the sciatic and tibial nerve was lowest in the sDPN group. Correspondingly, proximal 13

and distal ADC was highest in sDPN compared to patients with mDPN and nDPN as well as 14

HC. DTI-MRN correlated closely with the severity of neuropathy demonstrating strong 15

associations with sciatic and tibial nerve findings. Quantitative proton-spin-density group 16

differences were also significant but less pronounced than for DTI-MRN. 17

In conclusion, DTI-MRN enables detection of abnormalities in peripheral nerves related to 18

DPN and more so than proton-spin-density or T2-relaxation-time. These abnormalities are 19

likely to reflect pathology in sciatic and tibial nerve fibers. 20

21

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Introduction 1

Diabetic peripheral neuropathy (DPN) is a common complication that often remains 2

undiagnosed until later stages. DPN causes irreversible damage to the peripheral nerves. 3

Thus, to prevent progression of DPN, early diagnosis is important emphasizing the need for 4

more sensitive diagnostic techniques. 5

The DPN diagnosis is established based on a neurological examination, nerve conduction 6

studies (NCS), and quantitative sensory testing (QST). DPN is associated with structural 7

changes of the peripheral nerves including endoneurial microangiopathy (1), abnormal 8

Schwann cells (2), axonal degeneration (3), and paranodal demyelination leading to loss of 9

myelinated and unmyelinated fibers (4). 10

Peripheral nerve lesions can be visualized by ultrasonography (5–10) and magnetic resonance 11

neurography (MRN) (11–15). MRN enables microstructural imaging of peripheral nerves at 12

the anatomical level of the nerve fascicles. Using high field clinical scanners (3 Tesla) and 13

proton-spin-density or T2-weighted imaging sequences with fat suppression, an increased 14

MR signal has been shown in a variety of focal and non-focal neuropathies and 15

polyneuropathies (11–13,16). 16

Inclusion of diffusion-tensor-imaging (DTI) may improve the diagnostic accuracy of MRN in 17

the ulnar and median nerves (17,18). Furthermore, in a previous study on patients with severe 18

DPN we found that DTI is a highly reproducible method to detect severe DPN in patients 19

with type 1 diabetes (19). In the same pilot study, we found that the quantitative target 20

measures of DTI-MRN provided a more accurate group separation than quantitatively 21

evaluating changes based on T2 or proton-density contrast. This suggests that DTI may be the 22

most sensitive non-invasive imaging method to detect microstructural alterations of 23

peripheral nerves in DPN. 24

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The aim of the present study was to evaluate if MRN of the sciatic and tibial nerves can be 1

used for detection and staging of DPN in patients with type 1 diabetes. Furthermore, applying 2

receiver operating characteristic analyses we aimed to determine the sensitivity and 3

specificity of the MR methodology. 4

Research design and methods 5

This study was approved by the local ethics committee (No. 37251) and registered at clinical 6

trials (No. NCT01847937). All study participants gave informed consent. 7

Study population 8

We recruited 49 patients with type 1 diabetes from the Department of Endocrinology and 9

Internal Medicine and 30 healthy controls by public announcements. All participants were 10

examined between September 2013 and May 2016. Findings from 21 of these patients and 10 11

healthy controls have been reported in a previous feasibility study evaluating if DTI enabled 12

detection of DPN (19). That study only comprised patients with severe DPN and no 13

neuropathy. We now extend these findings by evaluating a larger cohort including patients 14

with milder DPN. All subjects included were aged 60-71 years. 15

The minimal criteria (20,21) determined the presence of diabetic neuropathy. Presence of 16

neuropathy is determined by at least two abnormal findings in the following four categories; 17

one of these categories had to be abnormal VPT or NCS: (1) abnormal vibratory perception 18

threshold (VPT) at index finger and great toe (≥98th

percentile), (2) abnormal nerve 19

recordings from nerve conduction studies (NCS) > 2, (3) neuropathy symptom scores (NSS) 20

> 1, and (4) neurological impairment scores (NIS) > 7. Subsequently, patients with diabetes 21

were divided into three groups: No neuropathy (nDPN), mild neuropathy (mDPN) (NIS < 24) 22

and severe neuropathy (sDPN) (NIS > 24). 23

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Exclusion criteria were severe cardiac or lung disease, acute or chronic musculoskeletal 1

disorders, acute metabolic dysregulation, other neurological or endocrine disorders, any 2

previous or present lower-limb asymmetric proximal weakness and contraindications to MRI. 3

Healthy controls filled in the Michigan Neuropathy Screening Instrument (MNSI) 4

questionnaire to exclude subjects with any symptoms of neuropathy and/or diabetes (22). 5

Blood samples 6

Blood samples were collected to measure the HbA1c (mmol/mol) using standard laboratory 7

methods. Plasma blood glucose was measured using a handheld glucose meter (FreeStyle 8

Lite, Abbot Diabetes Care, Copenhagen, Denmark). 9

Clinical examinations 10

Clinical examinations were performed by a trained neurologist using the NIS (23) and the 11

NSS. NIS is a combined score obtained from the neurological examination of muscle 12

strength, activity of tendon reflexes, and sensation at the great toe and index finger. NSS 13

includes motor, sensory or autonomic symptoms of neuropathy. 14

Vibration perception thresholds 15

VPT was performed at the distal part of the hallux and index finger using the 4-2-1 stepping 16

algorithm (CASE IV , WR Medical Electronics, Stillwater, MN, USA) (24,25). 17

Nerve conduction studies 18

NCS was performed with conventional surface electrode techniques at a skin temperature of 19

≥32°C using EMG-equipment (Keypoint version 2.11, Dantec, Skovlunde, Denmark). 20

Results were compared to laboratory controls. Motor NCS was performed in the median, 21

peroneal, and tibial nerves and conduction velocities (NCV) and compound muscle action 22

potential (CMAP) amplitudes were determined. Sensory NCV and sensory nerve action 23

potential (SNAP) amplitudes were determined in the median and sural nerves. The peroneal, 24

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tibial and sural nerves were examined bilaterally. The motor and sensory ulnar nerves were 1

included in persons with carpal tunnel syndrome. 2

Neuropathy rank sum score 3

To define the severity of neuropathy in each individual patient, we calculated a neuropathy 4

rank sum score (NRSS) based on the individual rank scores from the NIS, NSS, VPT and 5

NCS. 6

Magnetic resonance neurography 7

MR examinations were performed using a 3T MR-scanner (Skyra, Siemens AG, Erlangen, 8

Germany) with a 15-channel transmit/receive Knee Coil (Siemens AG, Erlangen, Germany). 9

MR images were acquired at the left leg at predetermined locations including the distal thigh 10

(10% of the distance from the upper part of the patella to the trochanter major) and the mid-11

calf level (50% of the distance from the lateral malleolus to the lower point of patella). The 12

proximal level (i.e. distal thigh) the entire sciatic nerve cross section was included as a 13

region-of-interest (ROI). This location will be referred to as “sciatic”, whereas the level at the 14

calf where the ROI only comprised fascicles of the tibial nerve will be referred to as “tibial”. 15

The MR protocol was performed unilaterally and consisted of spin-echo (SE) images with 10 16

different echo times and diffusion-weighted-images for calculation of diffusion parameters 17

(mean apparent diffusion coefficient (ADC), fractional anisotropy (FA) and trace). Analyses 18

of ADC and FA images were performed with nerve segmentation from the trace images 19

(Figure 1). MR images were acquired from the following pulse sequences: 20

1. Axial multi-echo SE SPAIR 2D sequence with a strong fat suppression pulse. TR = 21

3280ms, TE1-10 = [13, 25, 38, 51, 63, 76, 89, 101, 114, 127]ms, field of view (FOV) 22

160x160mm2, matrix size 512x512, slice thickness 3mm, voxel size 0.3x0.3x3 mm

3, 23

no inter-slice gap, 2 averages, and 16 slices, scan time = 22 min and 10 sec. 24

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2. Axial DWI weighted SE echo-planar imaging 2D sequence with a strong fat 1

suppression pulse. TR/TE 4200/112 ms, b = [0, 800]s/mm2, directions = 12, 4 2

averages, FOV 175x175 mm2, matrix size 128x128, slice thickness 3mm, voxel size 3

1.36x1.36x3 mm3, no inter-slice gap, and 16 slices, scan time = 3 min and 30 sec. 4

The net imaging time was 26 min 10 sec at each location with the inclusion of an anatomical 5

localizer (30 sec) scan at each location, a coil reposition requiring additionally 5 min. 6

Structural fiber loss is conceived as the dominant histological alteration of DPN and is 7

typically most severe distally (26) where it has been frequently evaluated in sural nerve 8

biopsies obtained at ankle level (27). To test a possible longitudinal gradient of fiber loss we 9

evaluated the ratio of the sciatic (proximal) level vs. the tibial (distal) level. 10

The cross-sectional area of the segmented nerves in the multi-SE images was used to evaluate 11

nerve caliber of the sciatic and tibial nerves. The multi-SE images had a higher resolution and 12

signal-to-noise ratio, providing improved structural visualization compared to DTI images. 13

Imaging processing and segmentation 14

FSL was used for processing and analyses of images (FMRIB Software Library, Oxford, UK) 15

(28). 16

Nerve lesion determination was based on quantitative analyses of signal intensities of the 17

sciatic and tibial nerves. Nerve segmentation was performed in the MR images with the 18

median echo time (TE = 63ms), providing a segmentation mask for the remaining multi-SE 19

images. T2-relaxation-time (T2) and proton-spin-density (PD) were calculated using a mono-20

exponential curve-fitting algorithm applied to the nerve signal intensities of the multi-SE 21

images. 22

Equation 1 23

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From the algorithm, k is the signal gain produced from the scanner and s0 is the true proton-1

spin-density. However, since k is difficult to separate from the true PD, the k and s0 are 2

combined and used as PD in this study. TE is the echo time. Mono-exponential parameters 3

were calculated from the 10 different echo times acquired from the multi-echo SE sequence 4

using MATLAB 2014a (MathWorks Inc., USA). 5

Statistics 6

The Student’s t-test was applied for pairwise comparison between single groups and one-way 7

ANOVA was applied to determine statistical differences between groups. Statistical 8

significance was defined as a two-tailed p-value of less than 0.05. Linear regression analyses 9

were performed to evaluate an association between the degree of neuropathy and the DTI 10

parameters. The goodness-of-fit of the linear approximation was determined with the 11

coefficient of determination described as the R2 value. Receiver operating characteristic 12

(ROC) analyses and area under the curve (AUC) of the FA and ADC values were calculated 13

with the following predefined AUC thresholds: 1.0-0.90 = excellent; 0.90-0.80 = good; 0.80-14

0.70 = fair; 0.70-0.60 = poor; 0.60-0.50 = fail (29). Statistical analyses were performed in 15

STATA 13.1 (StataCorp LP, College Station, TX, USA). 16

Results 17

Clinical examinations and demographics 18

The clinical and demographic results are presented in Table 1. 19

DTI-MRN 20

DTI 21

For DTI parameters of the sciatic nerve and tibial nerve, pairwise comparisons were 22

calculated (Figure 2). There were significant differences between groups indicating that FA 23

values decrease and ADC values increase according to severity of neuropathy in the groups 24

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(p < 0.01). No difference was observed comparing non-neuropathic patients with healthy 1

controls. 2

Sensitivity and specificity 3

Receiver operating characteristics (ROC) curves were calculated to determine AUC, 4

sensitivity and specificity of DTI to separate diabetic groups, in the following three analyses. 5

1. Patients with mild neuropathy compared to patients with no neuropathy. 6

2. Patients with severe neuropathy compared to patients with mild neuropathy 7

3. Patients with severe neuropathy compared to patients with no neuropathy 8

ROC curves were calculated for FA and ADC values at the sciatic and tibial nerves (Figure 9

3). Based on FA values there was a good separation between groups for the sciatic nerve 10

(AUC: 0.60-0.95) and for the tibial nerve (AUC: 0.69-0.90), respectively. Correspondingly, 11

for ADC values there was a good separation between the groups for the sciatic nerve (AUC: 12

0.63-0.70) as well as the tibial nerve (AUC: 0.59-0.78). 13

Associations between variables 14

Close correlations could be established between DTI parameters and severity of neuropathy 15

(NRSS) (FA: R2

= 0.32 and 0.49; ADC: R2

= 0.15 and 0.19) (tibial and sciatic nerves, 16

respectively) (Figure 4). 17

DTI parameters were related to the amplitude of the compound muscle action potential 18

(CMAP) (FA: R2 = 0.17 and 0.24; ADC: R

2 = 0.27 and 0.04) and the nerve conduction 19

velocity (NCV) of the peroneal + tibial (sciatic) and tibial nerve (FA: R2 = 0.18 and 0.37; 20

ADC: R2

= 0.31 and 0.22) (Table 2). Furthermore, we evaluated the relations between DTI 21

parameters and the NIS score (FA: R2 = 0.33 and 0.28; ADC: R

2 = 0.14 and 0.07) (Table 2). 22

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Distal-to-proximal gradient 1

The ratio between DTI findings from the distal (tibial) nerve and the proximal (sciatic) nerve 2

was similar in the groups as indicated by the FA ratio (HC: 0.87 ± 0.12; nDPN: 0.87 ± 0.14; 3

mDPN: 0.85 ± 0.15; sDPN: 0.81 ± 0.16) (p = 0.50) and the ADC ratio (HC: 1.04 ± 0.15; 4

nDPN: 1.04 ± 0.12; mDPN: 1.08 ± 0.24; sDPN: 1.11 ± 0.14) (p = 0.67). 5

However, there was a statistically significant difference in the distal-to-proximal gradient of 6

the FA values between the three groups; this was only found for the ADC values in the severe 7

neuropathy group (p = 0.05) (Table 3). 8

MR signal analyses 9

T2-relaxation-time and proton-spin-density 10

T2 and PD of the sciatic and tibial nerves showed no differences between groups (Table 4). 11

In pairwise analyses of the PD we found a difference between nDPN and sDPN in the sciatic 12

nerve (p = 0.03), a similar difference was found between nDPN and sDPN in the tibial nerve 13

(p = 0.03). 14

Nerve caliber 15

Cross-sectional areas were different between groups in the sciatic nerve and the tibial nerve 16

(Table 4). Paired sample t-tests revealed that the healthy control subjects had lower sciatic 17

nerve CSA compared with all groups of diabetics (p = 0.01). For the tibial nerve, the CSA 18

was different comparing nDPN and mDPN (p = 0.01) and also for HC compared to mDPN (p 19

= 0.04). 20

Discussion 21

We established that MRN is able to detect nerve abnormalities in patients with type 1 22

diabetes closely related to the severity of neuropathy suggesting that MRN can be used to 23

detect structural signs of neuropathy. We extended previous studies investigating MRN in 24

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DPN (11,12) by exclusively evaluating DPN of patients with type 1 diabetes in this study, 1

and importantly, by incorporating advanced MRN with diffusion-tensor-imaging also for the 2

first time. Our main finding is the superior diagnostic accuracy of quantitative DTI over 3

proton-spin-density or T2 values. In line with previous studies, we found that the structural 4

nerve differences as visualized by imaging appear most marked at the proximal rather than 5

the distal level. 6

In the Toronto criteria, NCS remains the gold standard for diagnosing and grading of DPN in 7

clinical research and new diagnostic methods should be compared and related to findings of 8

NCS (30). We established that MRN and NCS were closely associated suggesting that MRN 9

reflect the pathophysiological process of DPN in type 1 diabetes. In a previous study we 10

established that the MRN-DTI techniques applied are highly reproducible and reliable (19). 11

In our study, MR imaging included DTI (FA and ADC) and multi-echo SE imaging. FA and 12

ADC describe the restriction of water molecule diffusion in three dimensions. FA reflects the 13

spatial movement restriction and ADC reflects the diffusion speed of the water molecules. In 14

peripheral neuropathies, loss of axons and myelin leads to less constriction of endoneurial 15

flow along the nerves (31); this could explain the changes of FA and ADC. Experimental 16

studies have shown that FA correlates to the nerve fiber density (32–36). ADC changes in 17

relation to the membrane, myelin sheath, cell wall, macromolecule and viscosity alterations 18

in the low protein fluid flowing along the nerve fibers (31). In DPN, axonal loss is considered 19

the most prevalent pathological finding (3), suggesting FA is a good measure of DPN. 20

Presence and severity of neuropathy were determined from NCS, quantitative sensory 21

examinations and clinical examinations. Pairwise comparisons between the diabetic groups 22

and healthy controls showed that FA and ADC values of the sciatic and tibial nerves had the 23

highest discriminative power between no, subtle and severe DPN. The FA values differed 24

significantly between groups and even mild neuropathy could be separated from no 25

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neuropathy. Interestingly, this difference was more pronounced at the proximal/sciatic level 1

than at the distal level, which is also reflected by the AUC of the ROC analyses. The 2

proximal dominance of structural alteration in this study is consistent with previous studies 3

showing predominantly proximal structural nerve injury not only in DPN but also in other 4

polyneuropathies with similar distal symmetric symptoms (12,13). Diabetes patients without 5

neuropathy had similar ADC and FA values as healthy controls, stressing that the abnormal 6

FA and ADC values reflect neuropathic abnormalities rather than an effect of diabetes per se. 7

Based on the AUC from the FA and ADC values obtained at the proximal/sciatic level 8

(Figure 3), FA had the best discriminative performance compared to ADC. 9

Linear regression analyses demonstrated close associations between the severity of 10

neuropathy and the FA values of the sciatic and tibial nerves. The association was less 11

pronounced in relation to the ADC values. 12

Furthermore, FA and ADC of the sciatic and tibial nerves showed good associations to NCV 13

and CMAP, with the closest correlations for the FA values of the sciatic nerve. Evaluating the 14

relation between DTI and NIS, FA was more closely related than ADC. 15

DTI parameters have been used to evaluate axonal and myelin sheath integrity in the median 16

nerve in healthy subjects (37). These results were in part validated by indicating that FA and 17

ADC correlated with the integrity of the myelin sheath identifiers (NCV) and axial diffusivity 18

with fiber density/axonal integrity (CMAP) (18,38). In another study of patients with both 19

axonal and demyelinating neuropathies, the FA of the sciatic nerve was closely related to 20

CMAP (39). Thus, in this and in previous studies, FA enables more sensitive and accurate 21

detection of peripheral nerve abnormalities than ADC (40), irrespective of neuropathic 22

severity. 23

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Distal-to-proximal loss of axons was evaluated between and within groups from the DTI 1

parameters. We found a difference within groups in the proximal and distal FA values in line 2

with earlier findings (37). This underlines the importance of using predefined anatomical 3

scanning locations. 4

In our study, the cross-sectional area (CSA) of the sciatic nerve was lower in healthy controls 5

compared to patients. For the tibial nerve patients with mild neuropathy had larger CSA than 6

non-neuropathic patients, however, patients with severe neuropathy did not have larger CSA. 7

This is in contrast to findings using ultrasonography where enlarged nerves occurred distally 8

in advanced stages of neuropathy (5). The resolution used for segmentation of the CSA was 9

0.3 x 0.3 mm2 per pixel. Since the average nerve CSA of the tibial nerve is 7 mm

2, more than 10

75 pixels are used for segmentation (225 pixels in the sciatic nerve). This suggests that the 11

different findings using ultrasound and MRI cannot be explained by a lower resolution in 12

MRI. Our finding is consistent with previous studies showing that the increase of CSA occurs 13

predominantly at the proximal level in addition to DTI and signal alterations (12,13). 14

Ultrasonography is excellent for high-resolution imaging of superficial peripheral nerves; 15

however, not able to visualize deeply situated nerves, nerves surrounded by fat (sciatic nerve) 16

or nerves beneath bones (due to acoustic artefacts) (41,42). 17

Previous studies have shown that MRN is a more reliable measure for visualization of lesions 18

than ultrasonography (43). Nevertheless, since MRN is more expensive and time consuming, 19

ultrasonography may be a more feasible method. 20

To detect DPN, CSA determined by US is commonly used, however, hypoechogenity and 21

maximum thickness of nerve fascicles have also been evaluated (6,8). These studies indicated 22

a correlation between nerve conduction studies and ultrasound findings. However, other 23

studies have not been able to find a correlation between CSA and findings from nerve 24

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conduction studies (7,44). Ultrasonography may enable early detection of subclinical nerve 1

degeneration but by a higher resolution MRN may also be relevant. 2

In line with previous studies, the T2-relaxation-time had low discriminative power. 3

Interestingly, proton-spin-density was inferior to DTI for group discrimination. The relation 4

between abnormalities observed at DTI-MRN and the pathological process of neuropathy 5

remains unclear. Hyperglycemia leads to cellular nerve damage through mitochondrial 6

overload, polyol pathway-induced oxidative stress and inflammatory injury (45,46). T2-7

weighted images are sensitive to edema and fat. We applied a strong fat saturation pulse to 8

remove the epineural fat signal adjacent to the nerve fascicles, causing fat and connective 9

tissue to appear dark in the MR images. In diabetics , severely damaged nerve tissue is 10

replaced by connective tissue (47) and thereby appear dark in the SE images. This could 11

explain the absence of T2 changes in patients with severe DPN. 12

Previously, in a mixed group of type 1 and type 2 diabetics, the PD signal was higher in both 13

mild and severe neuropathy (12). In their study, T2-weighted and PD-weighted imaging were 14

applied, but with a normal fat saturation pulse over a larger area. This approach compared 15

with our study only including type 1 diabetics, might explain the difference in findings of PD. 16

Therefore, a study evaluating MRN in type 2 diabetes is necessary to evaluate possible 17

differences between the two types of diabetes. 18

Axonal loss would not result in altered signal intensity of the T2-weighted images (12,48). 19

Since FA is closely associated with fiber density (32–34), this may explain why FA values 20

are more closely related to the severity of neuropathy compared to T2 and PD. 21

Our study has several limitations. First, this is a cross-sectional study, and it thus remains 22

unknown how DTI findings develop over time. Secondly, axial and radial diffusivity was not 23

calculated in our study, which in healthy controls provide additional information about 24

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axonal and myelin sheath integrity (37). Thirdly, MRN coverage of the sciatic and tibial 1

nerves consisted of 16 slices (2 x 4.80 cm), evaluating only small parts of the nerve. MRN 2

covering the entire nerves would enable detection of multifocal lesions in DPN; however, this 3

would increase examination time considerably. Finally, we did not include the upper-limb 4

nerve to serve as a control for the lower-limb, which could have further substantiated our 5

findings; this would, however, also increase the examination time. Finally, the study did not 6

include an assessment of peripheral limb vascular status to evaluate any influence of 7

multifocal ischemic neuropathy on the DTI-MRN findings. 8

In conclusion, we found close associations between findings of DTI-MRN and the presence 9

and severity of neuropathy in proximal and distal nerve segments of patients with type 1 10

diabetes. DTI-MRN is a non-invasive, quantitative method which may be used to detect and 11

monitor the neuropathic processes in DPN. 12

Acknowledgements 13

The authors acknowledge Søren Gregersen (Department of Endocrinology and Internal 14

Medicine, Aarhus University Hospital) for helping with patient recruitment. 15

Funding 16

The author(s) disclosed receipt of the following financial support for the research, authorship, 17

and/or publication of this article: This work is funded by the UNIK partnership foundation, 18

Siemens A/G Copenhagen, the Danish Diabetes Academy 19

supported by the Novo Nordisk Foundation, Aarhus University and the BEVICA Foundation. 20

MP was supported by the Deutsche Forschungsgemeinschaft (SFB 1158, Project A3). SH 21

was supported by the Deutsche Forschungsgemeinschaft (SFB 1118 Project, B05). 22

Author Contributions 23

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MV, HA, NE, SH, and MP designed the study. HA and MV examined the patients. PLP and 1

MV recruited the patients. MV, HA, HT, SR performed the research and MV analyzed data 2

and drafted the manuscript. MV is the guarantor of this work and, as such, had full access to 3

all data during the study and takes responsibility for the integrity of the data and the accuracy 4

of the data analyses. 5

6

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Tables 1

Table 1 – Clinical data, nerve conduction studies (NCS) and quantitative sensory 2

examinations 3

Healthy

Controls

T1 diabetes

No DPN

T1 diabetes

Mild DPN

T1 diabetes

Severe DPN

N 30 25 13 11

Age (yrs) 64.3 ± 3.2 64.6 ± 3.6 64.7 ± 2.4 66.9 ± 3.5

Male (%) 15 (50) 11 (44) 7 (54) 9 (82)

BMI (kg/m2) 26.3 ± 4.4 25.0 ± 3.4 27.2 ± 4.2 28.0 ± 4.4

Diabetes duration (yrs)* - 30.0 ± 12 39.2 ± 15.0 43.7 ± 14.2

p-glucose (mmol/L)* - 8.9 ± 3.4 11 ± 2.6 12 ± 3.4

HbA1c (%) - 7.4 ± 0.9 7.8 ± 0.8 7.8 ± 0.7

HbA1c (mmol/mol) - 57.2 ± 10.0 61.8 ± 8.4 62.0 ± 7.9

NIS** - 6.4 ± 6.9 15.8 ± 5.3 32.7 ± 6.9

NSS** - 0.4 ± 0.6 1.4 ± 1.1 2.8 ± 2.3

VPT hand (percentile) - 81.7 ± 24.5 93.1 ± 7.5 93.3 ± 9.3

VPT foot (percentile) - 74.0 ± 20.4 76.6 ± 17.5 70.3 ± 26.9

Nerve Conduction Studies

Sural NCV** - -1.1 ± 0.8 -2.4 ± 0.8 -2.4 ± 1.3

Sural SNAP** - -0.5 ± 1.5 -3.1 ± 2.2 -3.8 ± 2.3

Median NCV (sensory) - -2.5 ± 2.0 -2.8 ± 1.1 -4.0 ± 2.2

Median SNAP - -2.7 ± 2.5 -3.3 ± 2.3 -4.1 ± 3.1

Tibial NCV** - -1.4 ± 1.0 -2.2 ± 1.4 -2.9 ± 1.3

Tibial CMAP** - -0.1 ± 1.0 -2.9 ± 4.1 -4.0 ± 4.7

Peroneal NCV** - -1.3 ± 1.1 -3.7 ± 3.8 -3.4 ± 2.0

Peroneal CMAP** - -0.1 ± 0.9 -2.6 ± 3.0 -3.4 ± 2.8

Median NCV (motor)* - -1.8 ± 1.1 -2.8 ± 0.8 -2.2 ± 1.5

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Median CMAP** - -0.4 ± 0.9 -0.3 ± 1.2 -1.8 ± 2.0

NCS mean** - -1.1 ± 0.7 -2.6 ± 1.2 -3.2 ± 1.8

Values are mean ± SD. Results from the nerve conduction studies are given in standard 1

deviations from mean of matched healthy controls (age, gender, height). Values from subject 2

groups were tested against the type 1 diabetics without neuropathy. NIS = neurological 3

impairment score, NSS = neuropathy symptom score, VPT = vibratory perception threshold, 4

NCV = nerve conduction velocity, SNAP = sensory nerve action potential, CMAP = 5

compound motor action potential. * p<0.05, ** p<0.01 6

7

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Table 2 – Associations between diffusion-tensor-imaging parameters (FA and ADC) and 1

(1) nerve conduction studies and (2) clinical examinations 2

Sciatic nerve Tibial nerve

R2-value p-value R

2-value p-value

FA vs CMAP 0.24 < 0.01 0.17 < 0.01

FA vs NCV 0.37 < 0.01 0.18 0.01

FA vs NIS 0.28 < 0.01 0.33 < 0.01

ADC vs CMAP 0.04 0.13 0.27 < 0.01

ADC vs NCV 0.22 0.01 0.31 < 0.01

ADC vs NIS 0.07 0.08 0.14 0.01

Nerve conduction studies consist of compound motor action potential (CMAP) and nerve 3

conduction velocity (NCV) of the peroneal and tibial nerves. Neurological impairment score 4

(NIS). Linear regression analyses were applied for correlation analyses. 5

6

7

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1

Table 3 – Distal-to-proximal gradients of FA and ADC values in healthy controls, type 1 2

diabetics with no neuropathy, mild and severe neuropathy 3

FA Sciatic Tibial Difference Difference CI p-value

HC 0.48 ± 0.06 0.42 ± 0.06 0.06 ± 0.06 0.04 ; 0.09 <0.01

No DPN 0.47 ± 0.04 0.41 ± 0.07 0.06 ± 0.06 0.03 ; 0.09 <0.01

Mild DPN 0.41 ± 0.07 0.34 ± 0.06 0.06 ± 0.06 0.03 ; 0.10 <0.01

Severe DPN 0.38 ± 0.04 0.31 ± 0.08 0.08 ± 0.06 0.03 ; 0.12 <0.01

ADC Sciatic Tibial Difference Difference CI p-value

HC 1.47 ± 0.16 1.52 ± 0.19 -0.05 ± 0.22 -0.14 ± 0.03 0.22

No DPN 1.52 ± 0.12 1.59 ± 0.19 -0.06 ± 0.19 -0.14 ; 0.02 0.12

Mild DPN 1.63 ± 0.26 1.74 ± 0.42 -0.11 ± 0.39 -0.35 ; 0.12 0.31

Severe DPN 1.62 ± 0.17 1.78 ± 0.20 -0.16 ± 0.22 -0.32 ; 0.00 0.05

Paired sample t-test. Values are mean ± SD. Confidence interval (CI) 95%. FA values are 4

without unit and ADC values are in 10-3

mm2/s. Healthy controls (HC). Diabetic 5

polyneuropathy (DPN). 6

7

8

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Table 4 – T2-relaxation-time, proton-spin-density and cross-sectional area of the sciatic 1

and tibial nerves in healthy controls, type 1 diabetes patients with no mild and severe 2

neuropathy (DPN) 3

Healthy

Controls

Type 1 Diabetes

No DPN

Type 1 Diabetes

Mild DPN

Type 1 Diabetes

Severe DPN

p-value

T2 sciatic 79 ± 8 83 ± 9 82 ± 16 83 ± 7 0.58

T2 tibial 61 ± 10 62 ± 9 63 ± 13 64 ± 6 0.80

PD sciatic 381 ± 80 403 ± 73 413 ± 124 343 ± 77 0.17

PD tibial 545 ± 112 570 ± 115 499 ± 149 484 ± 87 0.14

CSA sciatic 21 ± 6 27 ± 8 26 ± 5 28 ± 8 0.02

CSA tibial 7 ± 2 6 ± 2 9 ± 4 8 ± 3 0.04

ANOVA group analyses. Values are mean ± SD. T2 in ms and PD is unit less. Cross-4

sectional area (CSA) (mm2). Diabetic polyneuropathy (DPN). 5

6

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Figures 1

2

Figure 1 - Axial MR image (TR = 3280ms; TE = 63ms) (1st and 2nd row) and DTI-3

Trace images (3rd and 4th row) of the thigh (1st and 3rd row) and the shin (2nd and 4th 4

row) demonstrating the tibial nerve (T) and peroneal nerve (P) of a healthy control 5

subject (A), a diabetic patient without neuropathy (B), and a diabetic patient with 6

severe neuropathy (C). In A.1 a small blood vessel (V) is seen close to the nerves. A color 7

map has been applied to increase visual contrast in the DTI-Trace images. The MR 8

images indicate enlargement and signal hyper-intensity in the nerves of patients with 9

severe neuropathy (C), the difference being most pronounced for the sciatic nerve (C.1 10

and C.3). 11

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1 Figure 2 – Box plots of FA (top) and ADC (bottom) comparing healthy controls, type 1 2

diabetics with no neuropathy (No DPN), mild neuropathy (Mild DPN), and severe 3

neuropathy (Severe DPN). FA values are unit less and ADC values are 10-3mm

2/s. P-4

values represent statistical differences from pairwise comparisons (Student's t-test). The 5

plot illustrates the box (25th and 75th percentiles), whiskers (adjacent values), dots 6

(outliers) and median values of the groups. 7

8

of 30 Diabetes

1

2

Figure 3 - ROC curves of the sensitivity and specificity of FA (top row) and ADC 3

(bottom row) values in the sciatic and tibial nerves. Square = severe vs mild, Triangle = 4

mild vs no DPN, Circle = severe vs no DPN. 5

6 7

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1 Figure 4 - Linear regression analyses of FA (top row) and ADC (bottom row) values and 2

their association to neuropathy rank sum score (NRSS) in the sciatic (left column) and 3

tibial nerve (right column). 4

5

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Equations 1

Equation 1 – Mono-exponential equation used for fitting of nerve T2-relaxation-time (T2) and 2

nerve proton spin density (PD) 3

4 ( ) 0exp

2

TES TE ks

T

= ⋅ −

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magnetic resonance neurography visualizes abnormalities in ... · 9 schwann cells (2), axonal...

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