Longitudinal Analysis of Amyloid PET and Brain MRI for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: Findings from the ADNI Cohort
Abstract
:1. Introduction
2. Materials and Methods
2.1. Patients
2.2. AV-45 PET/CT and MRI
2.3. Quantitative PET Image Analysis
2.4. Quantitative Magnetic Resonance (MR) Image Analysis
2.5. Shape Features Considering Both PET and MR Images
2.6. Percent Change Compared at 2-Year Follow-Up
2.7. Statistical Analyses
3. Results
3.1. Patient Characteristics
3.2. Imaging Parameters
3.3. Receiver Operating Characteristic Curve Analysis
3.4. Percent Change Compared at 2-Year Follow-Up
3.5. Correlation of the Shape Feature with Cognitive Outcomes
4. Discussion
5. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Characteristics | Exclusion | Inclusion | p-Value |
---|---|---|---|
Number | 295 | 244 | |
Age (years) | 72.3 ± 7.8 | 71.0 ± 6.9 | 0.044 |
Sex | 0.470 | ||
Male | 159 (53.9) | 140 (57.4) | |
Female | 136 (46.1) | 104 (42.6) | |
Education (years) | 16.0 ± 2.6 | 16.4 ± 2.6 | 0.079 |
APOE4 | 0.188 | ||
0 | 155 (55.6) | 117 (48.1) | |
1 | 99 (35.5) | 96 (39.5) | |
2 | 25 (9.0) | 30 (12.3) | |
Diagnosis baseline | 0.077 | ||
EMCI | 197 (66.8) | 144 (59.0) | |
LMCI | 98 (33.2) | 100 (41.0) | |
CDR baseline | 0.49 ± 0.07 | 0.50 ± 0.05 | 0.303 |
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Characteristics | Nonconverters | Converters | p-Value | FDR-Corrected p-Value |
---|---|---|---|---|
Number | 104 | 76 | ||
Age (years) | 68.7 ± 6.8 | 73.1 ± 6.5 | <0.001 | 0.001 |
Sex | 0.933 | 0.933 | ||
Male | 57 (54.8) | 43 (56.6) | ||
Female | 47 (45.2) | 33 (43.4) | ||
Education (years) | 16.8 ± 2.4 | 16.1 ± 2.6 | 0.05 | 0.055 |
APOE4 | <0.001 | 0.001 | ||
0 | 65 (62.5) | 24 (31.6) | ||
1 | 29 (27.9) | 39 (51.3) | ||
2 | 10 (9.6) | 13 (17.1) | ||
Diagnosis baseline | <0.001 | 0.001 | ||
EMCI | 79 (76.0) | 28 (36.8) | ||
LMCI | 25 (24.0) | 48 (63.2) | ||
SUVR baseline | 1.11 ± 0.15 | 1.38 ± 0.22 | <0.001 | 0.001 |
AV-45 BASS baseline | 0.37 ± 0.05 | 0.44 ± 0.07 | <0.001 | 0.001 |
MRI BAI baseline | 3.78 ± 0.50 | 4.25 ± 0.47 | <0.001 | 0.001 |
Shape feature baseline | 1.40 ± 0.21 | 1.86 ± 0.29 | <0.001 | 0.001 |
CDR baseline | 0.50 ± 0.05 | 0.50 ± 0.00 | 0.394 | 0.414 |
ADAS-cog baseline | 11.67 ± 4.93 | 20.53 ± 6.69 | <0.001 | 0.001 |
FAQ baseline | 0.98 ± 1.92 | 5.99 ± 4.76 | <0.001 | 0.001 |
MMSE baseline | 28.56 ± 1.51 | 27.17 ± 1.75 | <0.001 | 0.001 |
2-year SUVR 2-year | 1.13 ± 0.17 | 1.40 ± 0.21 | <0.001 | 0.001 |
2-year AV-45 BASS | 0.38 ± 0.05 | 0.43 ± 0.06 | <0.001 | 0.001 |
2-year MRI BAI | 3.84 ± 0.51 | 4.47 ± 0.47 | <0.001 | 0.001 |
2-year shape feature | 1.45 ± 0.21 | 1.92 ± 0.27 | <0.001 | 0.001 |
2-year CDR | 0.35 ± 0.29 | 0.72 ± 0.32 | <0.001 | 0.001 |
2-year ADAS-cog | 10.71 ± 5.29 | 25.99 ± 9.59 | <0.001 | 0.001 |
2-year FAQ | 1.26 ± 1.88 | 12.25 ± 7.50 | <0.001 | 0.001 |
2-year MMSE | 28.21 ± 1.76 | 24.53 ± 3.46 | <0.001 | 0.001 |
Variables | AUC | 95% CI | Comparison of ROC Curves Between Each Variable and Shape Feature (p-Value) | Threshold | Sensitivity | Specificity | Youden’s J |
---|---|---|---|---|---|---|---|
Baseline | |||||||
Shape feature | 0.891 | 0.836–0.933 | - | 1.60 | 0.79 | 0.87 | 1.65 |
SUVR | 0.844 | 0.782–0.893 | 0.071 | 1.22 | 0.83 | 0.84 | 1.67 |
AV-45 BASS | 0.769 | 0.700–0.828 | <0.001 | 0.39 | 0.75 | 0.78 | 1.53 |
MRI BAI | 0.759 | 0.689–0.819 | <0.001 | 3.76 | 0.89 | 0.51 | 1.40 |
2 years | |||||||
Shape feature | 0.898 | 0.844–0.938 | - | 1.67 | 0.83 | 0.87 | 1.69 |
SUVR | 0.836 | 0.774–0.887 | 0.006 | 1.20 | 0.86 | 0.77 | 1.62 |
AV-45 BASS | 0.758 | 0.689–0.819 | <0.001 | 0.41 | 0.72 | 0.82 | 1.54 |
MRI BAI | 0.813 | 0.748–0.867 | 0.018 | 4.18 | 0.78 | 0.75 | 1.53 |
Characteristics | Nonconverters | Converters | p-Value | FDR-Corrected p-Value |
---|---|---|---|---|
Number | 104 | 76 | ||
Shape feature percent change (%) | 3.68 ± 6.94 | 3.91 ± 11.32 | 0.866 | 0.866 |
SUVR percent change (%) | 1.84 ± 5.39 | 1.64 ± 7.32 | 0.833 | 0.866 |
AV-45 BASS percent change (%) | 1.75 ± 5.19 | −1.28 ± 9.75 | 0.008 | 0.016 |
MRI BAI percent change (%) | 1.89 ± 4.15 | 5.31 ± 5.72 | <0.001 | 0.004 |
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Kim, D.-H. Longitudinal Analysis of Amyloid PET and Brain MRI for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: Findings from the ADNI Cohort. Tomography 2025, 11, 37. https://doi.org/10.3390/tomography11030037
Kim D-H. Longitudinal Analysis of Amyloid PET and Brain MRI for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: Findings from the ADNI Cohort. Tomography. 2025; 11(3):37. https://doi.org/10.3390/tomography11030037
Chicago/Turabian StyleKim, Do-Hoon. 2025. "Longitudinal Analysis of Amyloid PET and Brain MRI for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: Findings from the ADNI Cohort" Tomography 11, no. 3: 37. https://doi.org/10.3390/tomography11030037
APA StyleKim, D.-H. (2025). Longitudinal Analysis of Amyloid PET and Brain MRI for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease: Findings from the ADNI Cohort. Tomography, 11(3), 37. https://doi.org/10.3390/tomography11030037