Exploring the Potential of the Corpus Callosum Area as a Predictive Marker for Impaired Information Processing in Multiple Sclerosis
Abstract
:1. Introduction
2. Methods
2.1. Selection of Patients
2.2. Neuropsychological Tests
2.3. MRI Data Acquisition
2.4. CCA Measurement
2.5. Volumetric Neuroimaging Markers
2.6. DTI Neuroimaging Marker
2.7. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Overall | Cognitive Normal Group | Cognitive Impairment Group | ||
---|---|---|---|---|
n = 77 | n = 47 | n = 30 | p-value | |
mean (SD) | mean (SD) | mean (SD) | ||
Age, year | 47.94 (9.67) | 49.85 (9.16) | 44.93 (9.83) | <0.05 |
Sex, N, f/m | 54/23 | 36/11 | 18/12 | 0.56 |
Education year, year | 13.48 (2.17) | 13.60 (2.25) | 13.30 (2.05) | 0.82 |
EDSS, median | 4.50 (3) | 4.50 (4.00) | 4.50 (2.38) | 0.21 |
Disease duration, year | 13.13 (8.94) | 12.64 (10.36) | 13.90 (6.19) | 0.43 |
Subtype of MS, N, RR/SP/PP | 44/26/7 | 33/10/4 | 11/16/3 | <0.05 |
Callosal disconnection syndrome, N | 0 | 0 | 0 |
Overall | Cognitive Normal Group | Cognitive Impairment Group | ||
---|---|---|---|---|
n = 77 | n = 47 | n = 30 | p-value | |
mean (SD) | mean (SD) | mean (SD) | ||
SDMT z-score | −1.7 (1.6) | −0.6 (0.9) | −3.4 (1.0) | <0.001 |
PASAT 2 z-score | −1.2 (1.5) | −0.5 (1.1) | −2.2 (1.4) | <0.001 |
PASAT 1 z-score | −0.8 (1.2) | −0.2 (0.9) | −1.8 (1.0) | <0.001 |
WAIS VCI | 102.1 (14.3) | 107.4 (12.0) | 93.7 (13.8) | <0.001 |
WAIS PRI | 96.6 (16.9) | 102.9 (14.1) | 86.8 (16.4) | <0.001 |
WAIS WMI | 97.3 (15.4) | 104.2 (13.5) | 86.6 (11.9) | <0.001 |
WAIS PSI | 84.9 (19.8) | 96.1 (14.3) | 67.3 (13.3) | <0.001 |
WMS-R general memory | 95.3 (18.5) | 104.2 (13.2) | 81.5 (17.3) | <0.001 |
WMS-R delay recall | 91.8 (20.0) | 100.2 (15.0) | 78.6 (19.9) | <0.001 |
nCCA | 2.9 (0.9) | 3.3 (0.7) | 2.3 (0.8) | <0.001 |
corpus callosum, FA | 0.48 (0.08) | 0.52 (0.05) | 0.42 (0.07) | <0.001 |
cingulate gyrus, FA | 0.39 (0.06) | 0.42 (0.05) | 0.35 (0.06) | <0.001 |
brain parenchyma a | 70.1 (9.1) | 73.2 (8.3) | 65.3 (8.2) | <0.05 |
cortex a | 41.1 (5.0) | 42.2 (5.2) | 39.4 (4.4) | <0.05 |
thalamus a | 0.87 (0.17) | 0.95 (0.15) | 0.75 (0.13) | <0.001 |
cerebellum a | 9.1 (1.2) | 9.3 (1.4) | 8.7 (0.9) | 0.14 |
hippocampus a | 0.53 (0.09) | 0.55 (0.09) | 0.50 (0.08) | 0.55 |
putamen a | 0.55 (0.13) | 0.60 (0.10) | 0.48 (0.13) | <0.001 |
globus pallidus a | 0.25 (0.04) | 0.26 (0.04) | 0.24 (0.05) | <0.05 |
caudate a | 0.41 (0.08) | 0.43 (0.07) | 0.37 (0.07) | <0.05 |
lesion a | 1.0 (1.6) | 0.54 (0.81) | 1.8 (2.2) | <0.001 |
SDMT | PASAT 2 | PASAT 1 | WAIS VCI | WAIS PRI | WAIS WMI | WAIS PSI | WMS-R General Memory | WMS-R Delay Recall | EDSS | |
---|---|---|---|---|---|---|---|---|---|---|
nCCA | 0.60 * | 0.40 * | 0.54 * | 0.10 | 0.46 * | 0.49 * | 0.60 * | 0.61 * | 0.63 * | −0.26 * |
corpus callosum, FA | 0.67 * | 0.49 * | 0.59 * | 0.13 | 0.52 * | 0.55 * | 0.67 * | 0.63 * | 0.66 * | −0.24 * |
cingulate gyrus, FA | 0.65 * | 0.52 * | 0.56 * | 0.13 | 0.52 * | 0.58 * | 0.60 * | 0.59 * | 0.65 * | −0.21 |
brain parenchyma a | 0.43 * | 0.36 * | 0.49 * | 0.17 | 0.39 * | 0.44 * | 0.53 * | 0.46 * | 0.44 * | −0.20 |
cortex a | 0.26 * | 0.24 * | 0.33 * | 0.15 | 0.27 * | 0.33 * | 0.38 * | 0.26 * | 0.26 * | −0.22 |
thalamus a | 0.55 * | 0.42 * | 0.58 * | 0.23 * | 0.38 * | 0.46 * | 0.59 * | 0.56 * | 0.59 * | −0.22 |
cerebellum a | 0.19 | 0.10 | 0.25 * | 0.03 | 0.17 | 0.24 * | 0.27 * | 0.24 * | 0.16 | −0.14 |
hippocampus a | 0.25 * | 0.18 | 0.28 | 0.08 | 0.19 | 0.22 | 0.31 | 0.34 * | 0.36 * | −0.14 |
putamen a | 0.55 * | 0.48 * | 0.58 * | 0.22 | 0.47 * | 0.57 * | 0.56 * | 0.57 * | 0.62 * | −0.14 |
globus pallidus a | 0.23 * | 0.20 | 0.36 * | 0.12 | 0.18 | 0.29 * | 0.29 * | 0.31 * | 0.28 * | −0.10 |
caudate a | 0.36 * | 0.39 * | 0.44 * | 0.07 | 0.35 * | 0.36 * | 0.39 * | 0.49 * | 0.45 * | −0.12 |
lesion a | −0.62 * | −0.40 * | −0.45 * | −0.13 | −0.47 * | −0.39 * | −0.61 * | −0.66 * | −0.70 * | 0.30 * |
Sensitivity (%) | Specificity (%) | Cutoff | AUC | Youden Index | |
---|---|---|---|---|---|
nCCA | 80 | 83 | 2.86 | 0.82 | 0.63 |
corpus callosum, FA | 83 | 92 | 0.47 | 0.88 | 0.75 |
cingulate gyrus, FA | 90 | 72 | 0.41 | 0.85 | 0.62 |
brain parenchyma a | 57 | 87 | 65.5 | 0.76 | 0.44 |
cortex a | 57 | 70 | 39.7 | 0.64 | 0.27 |
thalamus a | 90 | 77 | 0.86 | 0.87 | 0.67 |
cerebellum a | 100 | 26 | 10.1 | 0.61 | 0.26 |
hippocampus a | 50 | 75 | 0.50 | 0.65 | 0.25 |
putamen a | 83 | 79 | 0.53 | 0.83 | 0.60 |
globus pallidus a | 50 | 89 | 0.22 | 0.66 | 0.39 |
caudate a | 63 | 81 | 0.37 | 0.73 | 0.44 |
lesion a | 77 | 85 | 0.91 | 0.86 | 0.62 |
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Akaike, S.; Okamoto, T.; Kurosawa, R.; Onodera, N.; Lin, Y.; Sato, W.; Yamamura, T.; Takahashi, Y. Exploring the Potential of the Corpus Callosum Area as a Predictive Marker for Impaired Information Processing in Multiple Sclerosis. J. Clin. Med. 2023, 12, 6948. https://doi.org/10.3390/jcm12216948
Akaike S, Okamoto T, Kurosawa R, Onodera N, Lin Y, Sato W, Yamamura T, Takahashi Y. Exploring the Potential of the Corpus Callosum Area as a Predictive Marker for Impaired Information Processing in Multiple Sclerosis. Journal of Clinical Medicine. 2023; 12(21):6948. https://doi.org/10.3390/jcm12216948
Chicago/Turabian StyleAkaike, Shun, Tomoko Okamoto, Ryoji Kurosawa, Nozomi Onodera, Youwei Lin, Wakiro Sato, Takashi Yamamura, and Yuji Takahashi. 2023. "Exploring the Potential of the Corpus Callosum Area as a Predictive Marker for Impaired Information Processing in Multiple Sclerosis" Journal of Clinical Medicine 12, no. 21: 6948. https://doi.org/10.3390/jcm12216948
APA StyleAkaike, S., Okamoto, T., Kurosawa, R., Onodera, N., Lin, Y., Sato, W., Yamamura, T., & Takahashi, Y. (2023). Exploring the Potential of the Corpus Callosum Area as a Predictive Marker for Impaired Information Processing in Multiple Sclerosis. Journal of Clinical Medicine, 12(21), 6948. https://doi.org/10.3390/jcm12216948