- Email: [email protected]
Apparent diffusion coefficient and diffusion-weighted signal intensity of the interpeduncle region of the midbrain in adults: initial evaluation
Clinical Imaging 37 (2013) 645–648
Contents lists available at SciVerse ScienceDirect
Clinical Imaging journal homepage: http://www.clinicalimaging.org
Apparent diffusion coefficient and diffusion-weighted signal intensity of the interpeduncle region of the midbrain in adults: initial evaluation☆ Deting Ma a, b,⁎, Cheng Liu a, Qingkui Kong b, Yuanzhong Xie b, Xuzhu Chen c a b c
Department of Radiology, Shandong Medical Imaging Research Institute, Shandong University, Jinan, 250021 P.R. China Department of Radiology, Taian Central Hospital, Taishan Medical University, Taian, 271000 P.R. China Department of Neuroimaging, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100050 P.R. China
a r t i c l e
i n f o
Article history: Received 4 July 2012 Received in revised form 3 November 2012 Accepted 21 February 2013 Keywords: Midbrain Signal intensity Diffusion-weighted imaging (DWI) Apparent diffusion coefficient (ADC)
a b s t r a c t Objective: The diffusion-weighted signal intensity (SI) of the interpeduncle region (IPR) of the midbrain has not been fully understood. This study was to evaluate the apparent diffusion coefficient (ADC) and SI of the IPR on axial diffusion-weighted imaging (DWI). Methods: Axial brain DWI (4-mm slice thickness, no gap) was performed in 145 healthy subjects at 1.5T MR scanner. Correlations between the contrast-to-noise ratio (CNR) and ADC value in the IPR and age, gender were statistically analyzed. Results: The CNR was significantly higher in the IPR than in the periaqueductal gray (PAG) (Pb.001). The CNR of the IPR positively correlated with age (P=.032) but not with gender (P=.091). The ADC value was significantly lower in the IPR than in the PAG (Pb.001). The ADC value of the IPR did not correlate with age (P=.522) or gender (P=.217). There was no correlation between the CNR and ADC value of the IPR (P=.622). Conclusions: The IPR usually shows high SI on DWI in healthy subjects, especially in older adults. DWI combined with the ADC maps would help to evaluate signal characteristics of the IPR. Crown Copyright © 2013 Published by Elsevier Inc. All rights reserved.
1. Introduction
2. Materials and methods
Diffusion-weighted imaging (DWI) has been proved to be a robust technique for the evaluation of a variety of neurologic diseases, such as hyperacute stroke [1–3], epilepsy [4], Alzheimer disease [5], multiple sclerosis [6–9], and Parkinson disease [10]. However, there are many regions of physiological hyperintensity on DWI of brain, for example, the cingulate gyrus and insula [11]. These signal intensity (SI) findings are not abnormal signs. In clinical practice, we have often encountered a high SI of the interpeduncle region (IPR) of midbrain from neurologically healthy adults on axial DWI—this would need to be mentioned and evaluated, as it would be much more useful to identify areas of abnormal diffusion optimally. To recognize abnormally increased SI in the IPR on DWI, the present study is to (a) describe qualitatively and quantitatively the signal characteristics of the IPR on axial DWI in neurologically healthy adults; (b) evaluate the effects of age and gender on the SI of the IPR; and (c) assess the correlation between apparent diffusion coefficient (ADC) value and age, gender, and contrast-to-noise ratio (CNR) of the IPR.
The institutional review board approved this retrospective study with waived informed consent.
☆ Disclosure: All authors have no conflicts of interest and source of funding. ⁎ Corresponding author. Department of Radiology, Taian, Central Hospital, 29#, Longtan Road, Taian, Shandong, 271000 P.R. China. E-mail address: [email protected] (D. Ma).
2.1. Patient population This retrospective study included 145 neurologically healthy subjects (70 males, 75 females; age range: 31–79 years; mean age: 48.7 years). The recruited criteria for study selection were normal findings at neurologic examination, no history of neurological disease, malignancy, stroke or brain surgery, and normal results brain magnetic resonance imaging. Indications for MR examination included headache (n=68), dizziness (n=45), and paresthesia (n=32). 2.2. Imaging procedures MR examinations were performed with a 1.5T superconducting system (Siemens Medical Systems, Avanto, Germany) with an eightchannel head coil. The MR imaging protocols were as follows: T1-fluid attenuation inversion recovery (FLAIR) (repetition time (TR)/echo time (TE)/ inversion time (TI)=2000/55/680 ms, one signal averaged, matrix= 256×256), T2-weighted fast spin-echo. (TR/TE=4000/99 ms, one signal averaged, matrix=256×256), turbo FLAIR (TR/TE/TI=9000/99/ 2500 ms, one signal averaged, matrix=256×256), and DWI (three-
0899-7071/$ – see front matter. Crown Copyright © 2013 Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.clinimag.2013.02.007
646
D. Ma et al. / Clinical Imaging 37 (2013) 645–648
Fig. 1. Axial DWI (TR/TE=3200/94 ms, b=1000 s/mm2, phase encoding direction with right to left) shows the positioning of ROIs in air, the TLWM, PAG, and IPR of the midbrain, respectively. Axial ADC map displays the positioning of ROI in IPR.
directional single-shot echo-planar imaging protocol, TR/TE=3200/ 94 ms, four signals averaged, b=0 and 1000 s/mm 2, matrix= 192×192) with parallel imaging (GeneRalized Auto-calibrating Partially Parallel Acquisition, GRAPPA). All routine sequences were performed on axial plane using identical parameters for number of slices, field of view (230 mm), phase encoding direction (right to left), slice thickness (4 mm), and no intersection gap. Axial DWI (b=1000 s/mm 2) and ADC map were used for quantitative analysis. 2.3. Image evaluation 2.3.1. Qualitative evaluation The IPR was identified at the ventral and inferior level of the midbrain, the rear of the interpeduncular fossa, the front of the periaqueductal gray (PAG) of midbrain. SI of the IPR was graded with a three-point scoring system: hypointense (Grade 1), isointense (Grade 2), and hyperintense (Grade 3) to the PAG of midbrain. The evaluation was conducted by two neuroradiologists (25 years and 22 years of experiences, respectively) independently. They were blind to each other and to the clinical information. Discrepancies of SI grading were resolved by consensus. SI of the PAG was compared with that of the IPR because the IPR and PAG are well depicted on the same section on the axial DWI. 2.3.2. Quantitative evaluation Region of interest (ROI) was performed on axial DWI and ADC map by a single investigator (neuroradiologist, 22 years of experiences),
who was blind to the clinical information. For quantitative interpretation, assessment of the SIs was done by placing circular ROIs in the IPR and the background of the images (Fig. 1). Circular ROIs with an optimal size (IPR: 20–25 pixels; PAG: 10–15 pixels) were hand placed on axial DWI. Background signal was measured in the temporal lobe white matter (TLWM) on the same image. Noise was defined as the standard deviation (S.D.) of the SI within an ROI outside the head (i.e., air). To measure the CNR, we used the formula CNR=[SI(IPR)−SI(b)]/ S.D. (noise), where SI(IPR) is the SI of the IPR and PAG, SI (b) the SI of the background and S.D. (noise) the S.D. of the SI of air. Therefore, the CNR of IPR to background and PAG to background were calculated. The ADC value of the IPR was also measured on axial ADC map (Fig. 1). The size of circular ROI in the IPR on the ADC map was copied from the corresponding DWI. 2.4. Statistical analysis The CNR and ADC value were compared between the IPR and the PAG by the paired-samples t test. One-way analysis of variance was used to evaluate the difference of the CNR and ADC value of IPR between males and females. Stepwise regression analysis was used to evaluate the effect of age on CNR and ADC value of the IPR and the correlation between CNR and ADC value of the IPR. P values less than .05 were considered statistically significant. Statistical analysis was performed with Statistical Package for the Social Sciences 16.0 for Windows.
Fig. 2. Axial DWI (TR/TE=3200/94 ms, b=1000 s/mm2, phase encoding direction with right to left) and corresponding ADC map without neurological findings. The IPR of the midbrain (IPR) displayed high signal in a 65-year-old woman (white arrow), relative to the PAG. The ADC value of the IPR was 0.67×10-3 mm2/s on the corresponding ADC map (black arrow).
D. Ma et al. / Clinical Imaging 37 (2013) 645–648
Fig. 3. CNR of the IPR of the midbrain (IPR) to that of the TLWM as a function of age. A positive correlation is depicted between CNR and age (P=.032).
647
Fig. 5. Stepwise regression analysis shows no significant correlation between ADC value and CNR of the IPR of the midbrain (IPR) (P=.622).
3. Results
4. Discussion
On DWI, the CNR was significantly higher in the IPR (29.53±7.65) than in the PAG (22.54±5.59) (t=17.084, Pb.001). A percentage of 65.5 (95/145) of the IPRs were Grade 3 (Fig. 2), and the remaining 34.5% (50/145) were Grade 2. In contrast, no subject manifested a Grade 1 in all 145 subjects. The CNR of the IPR significantly positively correlated with age (P=.032) (Fig. 3). In terms of gender-related differences in signals, the CNRs tended to be lower in the males (28.42 ±7.28) than in the females (30.57±7.88). This difference, however, was not significant (P=.091). In the ADC maps, the ADC values were significantly lower in the IPR ([0.698±0.037]×10 -3 mm 2/s, range, 0.617–0.794×10 -3 mm 2/s) than in the PAG ([0.741±0.043]×10 - 3 mm 2/s, range, 0.653– 0.855×10 -3 mm 2/s) (t=−12.537, Pb.001) (Fig. 2). In terms of genderand age-related differences in ADC values, there was no statistically significant difference between males ([0.702±0.037]×10 -3 mm 2/s) and females ([0.695±0.037]×10 -3 mm 2/s) in the IPR (P=.217). The ADC value of IPR did not correlate with age (P=.522) (Fig. 4). No significant correlation was revealed between ADC value and CNR in the IPR (P=.622) (Fig. 5).
We have performed a study of the signal characteristics of DWI of the IPR of normal brain on the axial plane. This study showed that the SI of the IPR significantly positively correlated with age but not with gender. Increased SI of the midbrain has been defined in certain diseases, such as cerebral infarction [1–3], epilepsy [4], and multiple sclerosis [6–9] and others. These diseases could be involved in the IPR. Their differentiation may be difficult because even in neurologically healthy subjects, the IPR frequently exhibited high SI, especially in older adults. Therefore, the identification of signal variations in the IPR on DWI is important for the diagnosis and assessment of neurological diseases. The SI on DWI is affected by many factors, including their T2, ADC, b value, spin attenuation, and TE [11,12]. The ADC of biological tissue is determined by many factors [11]. In this study, the ADC values of the IPR did not significantly change with aging, which was similar to previous study [13]. Our study also showed that there was no correlation between ADC value and the SI of the IPR and there were no gender-related differences on ADC value. These results may indicate that the ADC has not effected on the SI of the IPR on DWI. The decussation of the superior cerebellar peduncle (DSCP) was identified at the level of the inferior midbrain on the midsagittal T1WI with an ill-defined low signal area [14]. Therefore, the DSCP may be included in the IPR and may affect the spin attenuation. Absolute ADC values may be used to identify the ischemic tissue precisely [13,15] when focal and diffuse abnormalities are suspected because minor changes may be difficult to be detected by visual inspection [13]. In patients with acute stroke, ADC values in the hyperacute (6 h after onset) ischemic lesion were less than 0.63×10 -3 mm 2/s [16,17]. In our study, the mean ADC values were (0.698±0.037)×10 -3 mm 2/s (range, 0.617–0.794×10 -3 mm 2/s) in the IPR, in accordance with the findings in hyperacute stroke studies. In previous study, the ADC values in the white matter were 0.70±0.03×10 -3 mm 2/s (range, 0.62–0.79×10 -3 mm 2/s), and those in the gray matter were 0.89±0.04×10 -3 mm 2/s (range, 0.78– 1.09×10 -3 mm 2/s) [13]. Therefore, our results were consistent with the ADC values in the white matter, probably because of their structural properties, for example, the DSCP. There are several limitations in this study. Firstly, the ROIs (quantitative analysis) are simple round ROIs. Proper polygonalshaped ROIs should be used to minimize partial voluming around the edges. Secondly, no histologic specimens of the IPR were obtained. The relationship between SI of DWI and histology of the IPR remains unknown. Thirdly, the quantitative analysis was used as an absolute
Fig. 4. Stepwise regression analysis shows no significant correlation between ADC value of the IPR of the midbrain (IPR) and age (P=.522).
648
D. Ma et al. / Clinical Imaging 37 (2013) 645–648
CNR measure rather than a CNR index. Finally, neither sagittal, coronal plane nor diffusion tensor imaging was performed. In conclusion, the IPR frequently displays high SI on DWI in the neurologically normal brain, especially in older adults. Therefore, the regional signal variation should not be negligible when evaluating signal characteristics of the IPR on DWI. DWI combined with the ADC maps would help to evaluate signal characteristics of the IPR. References [1] Fung SH, Roccatagliata L, Gonzalez RG, Schaefer PW. MR diffusion imaging in ischemic stroke. Neuroimaging Clin N Am 2011;21(2):345–77xi. [2] Knash M, Tsang A, Hameed B, Saini M, Jeerakathil T, Beaulieu C, et al. Low cerebral blood volume is predictive of diffusion restriction only in hyperacute stroke. Stroke 2010;41(12):2795–800. [3] Wessels T, Wessels C, Ellsiepen A, Reuter I, Trittmacher S, Stolz E, et al. Contribution of diffusion-weighted imaging in determination of stroke etiology. AJNR Am J Neuroradiol 2006;27(1):35–9. [4] Kanner AM. Diffusion-weighted imaging: can it play a role in the evaluation of patients with epilepsy? Epilepsy Curr 2006;6(4):121–3. [5] Hanyu H, Sakurai H, Iwamoto T, Takasaki M, Shindo H, Abe K. Diffusionweighted MR imaging of the hippocampus and temporal white matter in Alzheimer’s disease. J Neurol Sci 1998;156(2):195–200. [6] Hygino da Cruz LC, Batista RR, Domingues RC, Barkhof F. Diffusion magnetic resonance imaging in multiple sclerosis. Neuroimaging Clin N Am 2011; 21(1): 71–88, vii-viii. [7] Balashov KE, Aung LL, Dhib-Jalbut S, Keller IA. Acute multiple sclerosis lesion: conversion of restricted diffusion due to vasogenic edema. J Neuroimaging 2011;21(2):202–4.
[8] Tievsky AL, Ptak T, Farkas J. Investigation of apparent diffusion coefficient and diffusion tensor anisotropy in acute and chronic multiple sclerosis lesions. AJNR Am J Neuroradiol 1999;20(8):1491–9. [9] Cercignani M, Iannucci G, Rocca MA, Comi G, Horsfield MA, Filippi M. Pathologic damage in MS assessed by diffusion-weighted and magnetization transfer MRI. Neurology 2000;54(5):1139–44. [10] Adachi M, Hosoya T, Haku T, Yamaguchi K, Kawanami T. Evaluation of the substantia nigra in patients with Parkinsonian syndrome accomplished using multishot diffusion-weighted MR imaging. AJNR Am J Neuroradiol 1999;20(8): 1500–6. [11] Asao C, Hirai T, Yoshimatsu S, Matsukawa T, Imuta M, Sagara K, et al. Human cerebral cortices: signal variation on diffusion-weighted MR imaging. Neuroradiology 2008;50(3):205–11. [12] Hiwatashi A, Kinoshita T, Moritani T, Wang HZ, Shrier DA, Numaguchi Y, et al. Hypointensity on diffusion-weighted MRI of the brain related to T2 shortening and susceptibility effects. AJR Am J Roentgenol 2003;181(6):1705–9. [13] Helenius J, Soinne L, Perkiö J, Salonen O, Kangasmäki A, Kaste M, et al. Diffusionweighted MR imaging in normal human brains in various age groups. AJNR Am J Neuroradiol 2002;23(2):194–9. [14] Spampinato MV, Kraas J, Maria BL, Walton ZJ, Rumboldt Z. Absence of decussation of the superior cerebellar peduncles in patients with Joubert syndrome. Am J Med Genet A 2008;146A(11):1389–94. [15] Dardzinski BJ, Sotak CH, Fisher M, Hasegawa Y, Li L, Minematsu K. Apparent diffusion coefficient mapping of experimental focal cerebral ischemia using diffusion-weighted echo-planar imaging. Magn Reson Med 1993;30(3): 318–25. [16] Marks MP, de Crespigny A, Lentz D, Enzmann DR, Albers GW, Moseley ME. Acute and chronic stroke: navigated spin-echo diffusion-weighted MR imaging. Radiology 1996;199(2):403–8. [17] Nagesh V, Welch KM, Windham JP, Patel S, Levine SR, Hearshen D, et al. Time course of ADCw changes in ischemic stroke: beyond the human eye! Stroke 1998;29(9):1778–82.
Contents lists available at SciVerse ScienceDirect
Clinical Imaging journal homepage: http://www.clinicalimaging.org
Apparent diffusion coefficient and diffusion-weighted signal intensity of the interpeduncle region of the midbrain in adults: initial evaluation☆ Deting Ma a, b,⁎, Cheng Liu a, Qingkui Kong b, Yuanzhong Xie b, Xuzhu Chen c a b c
Department of Radiology, Shandong Medical Imaging Research Institute, Shandong University, Jinan, 250021 P.R. China Department of Radiology, Taian Central Hospital, Taishan Medical University, Taian, 271000 P.R. China Department of Neuroimaging, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100050 P.R. China
a r t i c l e
i n f o
Article history: Received 4 July 2012 Received in revised form 3 November 2012 Accepted 21 February 2013 Keywords: Midbrain Signal intensity Diffusion-weighted imaging (DWI) Apparent diffusion coefficient (ADC)
a b s t r a c t Objective: The diffusion-weighted signal intensity (SI) of the interpeduncle region (IPR) of the midbrain has not been fully understood. This study was to evaluate the apparent diffusion coefficient (ADC) and SI of the IPR on axial diffusion-weighted imaging (DWI). Methods: Axial brain DWI (4-mm slice thickness, no gap) was performed in 145 healthy subjects at 1.5T MR scanner. Correlations between the contrast-to-noise ratio (CNR) and ADC value in the IPR and age, gender were statistically analyzed. Results: The CNR was significantly higher in the IPR than in the periaqueductal gray (PAG) (Pb.001). The CNR of the IPR positively correlated with age (P=.032) but not with gender (P=.091). The ADC value was significantly lower in the IPR than in the PAG (Pb.001). The ADC value of the IPR did not correlate with age (P=.522) or gender (P=.217). There was no correlation between the CNR and ADC value of the IPR (P=.622). Conclusions: The IPR usually shows high SI on DWI in healthy subjects, especially in older adults. DWI combined with the ADC maps would help to evaluate signal characteristics of the IPR. Crown Copyright © 2013 Published by Elsevier Inc. All rights reserved.
1. Introduction
2. Materials and methods
Diffusion-weighted imaging (DWI) has been proved to be a robust technique for the evaluation of a variety of neurologic diseases, such as hyperacute stroke [1–3], epilepsy [4], Alzheimer disease [5], multiple sclerosis [6–9], and Parkinson disease [10]. However, there are many regions of physiological hyperintensity on DWI of brain, for example, the cingulate gyrus and insula [11]. These signal intensity (SI) findings are not abnormal signs. In clinical practice, we have often encountered a high SI of the interpeduncle region (IPR) of midbrain from neurologically healthy adults on axial DWI—this would need to be mentioned and evaluated, as it would be much more useful to identify areas of abnormal diffusion optimally. To recognize abnormally increased SI in the IPR on DWI, the present study is to (a) describe qualitatively and quantitatively the signal characteristics of the IPR on axial DWI in neurologically healthy adults; (b) evaluate the effects of age and gender on the SI of the IPR; and (c) assess the correlation between apparent diffusion coefficient (ADC) value and age, gender, and contrast-to-noise ratio (CNR) of the IPR.
The institutional review board approved this retrospective study with waived informed consent.
☆ Disclosure: All authors have no conflicts of interest and source of funding. ⁎ Corresponding author. Department of Radiology, Taian, Central Hospital, 29#, Longtan Road, Taian, Shandong, 271000 P.R. China. E-mail address: [email protected] (D. Ma).
2.1. Patient population This retrospective study included 145 neurologically healthy subjects (70 males, 75 females; age range: 31–79 years; mean age: 48.7 years). The recruited criteria for study selection were normal findings at neurologic examination, no history of neurological disease, malignancy, stroke or brain surgery, and normal results brain magnetic resonance imaging. Indications for MR examination included headache (n=68), dizziness (n=45), and paresthesia (n=32). 2.2. Imaging procedures MR examinations were performed with a 1.5T superconducting system (Siemens Medical Systems, Avanto, Germany) with an eightchannel head coil. The MR imaging protocols were as follows: T1-fluid attenuation inversion recovery (FLAIR) (repetition time (TR)/echo time (TE)/ inversion time (TI)=2000/55/680 ms, one signal averaged, matrix= 256×256), T2-weighted fast spin-echo. (TR/TE=4000/99 ms, one signal averaged, matrix=256×256), turbo FLAIR (TR/TE/TI=9000/99/ 2500 ms, one signal averaged, matrix=256×256), and DWI (three-
0899-7071/$ – see front matter. Crown Copyright © 2013 Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.clinimag.2013.02.007
646
D. Ma et al. / Clinical Imaging 37 (2013) 645–648
Fig. 1. Axial DWI (TR/TE=3200/94 ms, b=1000 s/mm2, phase encoding direction with right to left) shows the positioning of ROIs in air, the TLWM, PAG, and IPR of the midbrain, respectively. Axial ADC map displays the positioning of ROI in IPR.
directional single-shot echo-planar imaging protocol, TR/TE=3200/ 94 ms, four signals averaged, b=0 and 1000 s/mm 2, matrix= 192×192) with parallel imaging (GeneRalized Auto-calibrating Partially Parallel Acquisition, GRAPPA). All routine sequences were performed on axial plane using identical parameters for number of slices, field of view (230 mm), phase encoding direction (right to left), slice thickness (4 mm), and no intersection gap. Axial DWI (b=1000 s/mm 2) and ADC map were used for quantitative analysis. 2.3. Image evaluation 2.3.1. Qualitative evaluation The IPR was identified at the ventral and inferior level of the midbrain, the rear of the interpeduncular fossa, the front of the periaqueductal gray (PAG) of midbrain. SI of the IPR was graded with a three-point scoring system: hypointense (Grade 1), isointense (Grade 2), and hyperintense (Grade 3) to the PAG of midbrain. The evaluation was conducted by two neuroradiologists (25 years and 22 years of experiences, respectively) independently. They were blind to each other and to the clinical information. Discrepancies of SI grading were resolved by consensus. SI of the PAG was compared with that of the IPR because the IPR and PAG are well depicted on the same section on the axial DWI. 2.3.2. Quantitative evaluation Region of interest (ROI) was performed on axial DWI and ADC map by a single investigator (neuroradiologist, 22 years of experiences),
who was blind to the clinical information. For quantitative interpretation, assessment of the SIs was done by placing circular ROIs in the IPR and the background of the images (Fig. 1). Circular ROIs with an optimal size (IPR: 20–25 pixels; PAG: 10–15 pixels) were hand placed on axial DWI. Background signal was measured in the temporal lobe white matter (TLWM) on the same image. Noise was defined as the standard deviation (S.D.) of the SI within an ROI outside the head (i.e., air). To measure the CNR, we used the formula CNR=[SI(IPR)−SI(b)]/ S.D. (noise), where SI(IPR) is the SI of the IPR and PAG, SI (b) the SI of the background and S.D. (noise) the S.D. of the SI of air. Therefore, the CNR of IPR to background and PAG to background were calculated. The ADC value of the IPR was also measured on axial ADC map (Fig. 1). The size of circular ROI in the IPR on the ADC map was copied from the corresponding DWI. 2.4. Statistical analysis The CNR and ADC value were compared between the IPR and the PAG by the paired-samples t test. One-way analysis of variance was used to evaluate the difference of the CNR and ADC value of IPR between males and females. Stepwise regression analysis was used to evaluate the effect of age on CNR and ADC value of the IPR and the correlation between CNR and ADC value of the IPR. P values less than .05 were considered statistically significant. Statistical analysis was performed with Statistical Package for the Social Sciences 16.0 for Windows.
Fig. 2. Axial DWI (TR/TE=3200/94 ms, b=1000 s/mm2, phase encoding direction with right to left) and corresponding ADC map without neurological findings. The IPR of the midbrain (IPR) displayed high signal in a 65-year-old woman (white arrow), relative to the PAG. The ADC value of the IPR was 0.67×10-3 mm2/s on the corresponding ADC map (black arrow).
D. Ma et al. / Clinical Imaging 37 (2013) 645–648
Fig. 3. CNR of the IPR of the midbrain (IPR) to that of the TLWM as a function of age. A positive correlation is depicted between CNR and age (P=.032).
647
Fig. 5. Stepwise regression analysis shows no significant correlation between ADC value and CNR of the IPR of the midbrain (IPR) (P=.622).
3. Results
4. Discussion
On DWI, the CNR was significantly higher in the IPR (29.53±7.65) than in the PAG (22.54±5.59) (t=17.084, Pb.001). A percentage of 65.5 (95/145) of the IPRs were Grade 3 (Fig. 2), and the remaining 34.5% (50/145) were Grade 2. In contrast, no subject manifested a Grade 1 in all 145 subjects. The CNR of the IPR significantly positively correlated with age (P=.032) (Fig. 3). In terms of gender-related differences in signals, the CNRs tended to be lower in the males (28.42 ±7.28) than in the females (30.57±7.88). This difference, however, was not significant (P=.091). In the ADC maps, the ADC values were significantly lower in the IPR ([0.698±0.037]×10 -3 mm 2/s, range, 0.617–0.794×10 -3 mm 2/s) than in the PAG ([0.741±0.043]×10 - 3 mm 2/s, range, 0.653– 0.855×10 -3 mm 2/s) (t=−12.537, Pb.001) (Fig. 2). In terms of genderand age-related differences in ADC values, there was no statistically significant difference between males ([0.702±0.037]×10 -3 mm 2/s) and females ([0.695±0.037]×10 -3 mm 2/s) in the IPR (P=.217). The ADC value of IPR did not correlate with age (P=.522) (Fig. 4). No significant correlation was revealed between ADC value and CNR in the IPR (P=.622) (Fig. 5).
We have performed a study of the signal characteristics of DWI of the IPR of normal brain on the axial plane. This study showed that the SI of the IPR significantly positively correlated with age but not with gender. Increased SI of the midbrain has been defined in certain diseases, such as cerebral infarction [1–3], epilepsy [4], and multiple sclerosis [6–9] and others. These diseases could be involved in the IPR. Their differentiation may be difficult because even in neurologically healthy subjects, the IPR frequently exhibited high SI, especially in older adults. Therefore, the identification of signal variations in the IPR on DWI is important for the diagnosis and assessment of neurological diseases. The SI on DWI is affected by many factors, including their T2, ADC, b value, spin attenuation, and TE [11,12]. The ADC of biological tissue is determined by many factors [11]. In this study, the ADC values of the IPR did not significantly change with aging, which was similar to previous study [13]. Our study also showed that there was no correlation between ADC value and the SI of the IPR and there were no gender-related differences on ADC value. These results may indicate that the ADC has not effected on the SI of the IPR on DWI. The decussation of the superior cerebellar peduncle (DSCP) was identified at the level of the inferior midbrain on the midsagittal T1WI with an ill-defined low signal area [14]. Therefore, the DSCP may be included in the IPR and may affect the spin attenuation. Absolute ADC values may be used to identify the ischemic tissue precisely [13,15] when focal and diffuse abnormalities are suspected because minor changes may be difficult to be detected by visual inspection [13]. In patients with acute stroke, ADC values in the hyperacute (6 h after onset) ischemic lesion were less than 0.63×10 -3 mm 2/s [16,17]. In our study, the mean ADC values were (0.698±0.037)×10 -3 mm 2/s (range, 0.617–0.794×10 -3 mm 2/s) in the IPR, in accordance with the findings in hyperacute stroke studies. In previous study, the ADC values in the white matter were 0.70±0.03×10 -3 mm 2/s (range, 0.62–0.79×10 -3 mm 2/s), and those in the gray matter were 0.89±0.04×10 -3 mm 2/s (range, 0.78– 1.09×10 -3 mm 2/s) [13]. Therefore, our results were consistent with the ADC values in the white matter, probably because of their structural properties, for example, the DSCP. There are several limitations in this study. Firstly, the ROIs (quantitative analysis) are simple round ROIs. Proper polygonalshaped ROIs should be used to minimize partial voluming around the edges. Secondly, no histologic specimens of the IPR were obtained. The relationship between SI of DWI and histology of the IPR remains unknown. Thirdly, the quantitative analysis was used as an absolute
Fig. 4. Stepwise regression analysis shows no significant correlation between ADC value of the IPR of the midbrain (IPR) and age (P=.522).
648
D. Ma et al. / Clinical Imaging 37 (2013) 645–648
CNR measure rather than a CNR index. Finally, neither sagittal, coronal plane nor diffusion tensor imaging was performed. In conclusion, the IPR frequently displays high SI on DWI in the neurologically normal brain, especially in older adults. Therefore, the regional signal variation should not be negligible when evaluating signal characteristics of the IPR on DWI. DWI combined with the ADC maps would help to evaluate signal characteristics of the IPR. References [1] Fung SH, Roccatagliata L, Gonzalez RG, Schaefer PW. MR diffusion imaging in ischemic stroke. Neuroimaging Clin N Am 2011;21(2):345–77xi. [2] Knash M, Tsang A, Hameed B, Saini M, Jeerakathil T, Beaulieu C, et al. Low cerebral blood volume is predictive of diffusion restriction only in hyperacute stroke. Stroke 2010;41(12):2795–800. [3] Wessels T, Wessels C, Ellsiepen A, Reuter I, Trittmacher S, Stolz E, et al. Contribution of diffusion-weighted imaging in determination of stroke etiology. AJNR Am J Neuroradiol 2006;27(1):35–9. [4] Kanner AM. Diffusion-weighted imaging: can it play a role in the evaluation of patients with epilepsy? Epilepsy Curr 2006;6(4):121–3. [5] Hanyu H, Sakurai H, Iwamoto T, Takasaki M, Shindo H, Abe K. Diffusionweighted MR imaging of the hippocampus and temporal white matter in Alzheimer’s disease. J Neurol Sci 1998;156(2):195–200. [6] Hygino da Cruz LC, Batista RR, Domingues RC, Barkhof F. Diffusion magnetic resonance imaging in multiple sclerosis. Neuroimaging Clin N Am 2011; 21(1): 71–88, vii-viii. [7] Balashov KE, Aung LL, Dhib-Jalbut S, Keller IA. Acute multiple sclerosis lesion: conversion of restricted diffusion due to vasogenic edema. J Neuroimaging 2011;21(2):202–4.
[8] Tievsky AL, Ptak T, Farkas J. Investigation of apparent diffusion coefficient and diffusion tensor anisotropy in acute and chronic multiple sclerosis lesions. AJNR Am J Neuroradiol 1999;20(8):1491–9. [9] Cercignani M, Iannucci G, Rocca MA, Comi G, Horsfield MA, Filippi M. Pathologic damage in MS assessed by diffusion-weighted and magnetization transfer MRI. Neurology 2000;54(5):1139–44. [10] Adachi M, Hosoya T, Haku T, Yamaguchi K, Kawanami T. Evaluation of the substantia nigra in patients with Parkinsonian syndrome accomplished using multishot diffusion-weighted MR imaging. AJNR Am J Neuroradiol 1999;20(8): 1500–6. [11] Asao C, Hirai T, Yoshimatsu S, Matsukawa T, Imuta M, Sagara K, et al. Human cerebral cortices: signal variation on diffusion-weighted MR imaging. Neuroradiology 2008;50(3):205–11. [12] Hiwatashi A, Kinoshita T, Moritani T, Wang HZ, Shrier DA, Numaguchi Y, et al. Hypointensity on diffusion-weighted MRI of the brain related to T2 shortening and susceptibility effects. AJR Am J Roentgenol 2003;181(6):1705–9. [13] Helenius J, Soinne L, Perkiö J, Salonen O, Kangasmäki A, Kaste M, et al. Diffusionweighted MR imaging in normal human brains in various age groups. AJNR Am J Neuroradiol 2002;23(2):194–9. [14] Spampinato MV, Kraas J, Maria BL, Walton ZJ, Rumboldt Z. Absence of decussation of the superior cerebellar peduncles in patients with Joubert syndrome. Am J Med Genet A 2008;146A(11):1389–94. [15] Dardzinski BJ, Sotak CH, Fisher M, Hasegawa Y, Li L, Minematsu K. Apparent diffusion coefficient mapping of experimental focal cerebral ischemia using diffusion-weighted echo-planar imaging. Magn Reson Med 1993;30(3): 318–25. [16] Marks MP, de Crespigny A, Lentz D, Enzmann DR, Albers GW, Moseley ME. Acute and chronic stroke: navigated spin-echo diffusion-weighted MR imaging. Radiology 1996;199(2):403–8. [17] Nagesh V, Welch KM, Windham JP, Patel S, Levine SR, Hearshen D, et al. Time course of ADCw changes in ischemic stroke: beyond the human eye! Stroke 1998;29(9):1778–82.