Correlation between F18-FDG PET/CT Imaging and BRAF V600E Genetic Mutation for the Early Assessment of Treatment Response in Papillary Thyroid Cancers
Abstract
:1. Introduction
2. Patients and Method
2.1. Patients
2.2. Genetic Analysis
2.3. Positron Emission Tomography/Computed Tomography (PET/CT) Imaging
2.4. Serologic Analysis
2.5. Statistics
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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No | Sex | BRAF status | SUV | Age yo | T | N | M | L | V | R | EET | Stage |
---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | M | + | 21.57 | 69 | T4a | N1b | 0 | 1 | 1 | 1 | Yes | III |
2 | M | + | 16.57 | 72 | T3b | N1b | 0 | 1 | 0 | 1 | Yes | II |
3 | M | - | 4.8 | 53 | T3b | N1b | 0 | 0 | 1 | 1 | Yes | II |
4 | F | - | 17.09 | 62 | T2 | N1b | 0 | 1 | 0 | 0 | Yes | II |
5 | F | + | 2.86 | 58 | T3b | N1b | 0 | 0 | 0 | 0 | Yes | II |
6 | F | + | 15 | 60 | T4a | N1b | 0 | 1 | 1 | 1 | Yes | III |
7 | F | - | 3.76 | 39 | T3a | N1b | 0 | 0 | 0 | 0 | Yes | I |
8 | M | + | 5.7 | 41 | T3b | N1b | 0 | 1 | 0 | 1 | Yes | I |
9 | M | + | 2.6 | 63 | T1a | N0 | 0 | 0 | 0 | 0 | Yes | I |
10. | F | - | 3.94 | 61 | T2 | N1b | 0 | 1 | 0 | 1 | Yes | II |
11. | F | N/a | 3.11 | 62 | T2 | N1b | 0 | 0 | 0 | 0 | No | I |
12. | F | + | 2.56 | 66 | T4a | N1b | 0 | 0 | 0 | 1 | Yes | III |
13. | M | - | 4.68 | 22 | T3a | N1b | 0 | 1 | 1 | 1 | Yes | I |
14. | F | - | 4.82 | 71 | T3b | N0 | 0 | 0 | 1 | 0 | Yes | II |
15. | F | - | 17.78 | 72 | T3b | N1b | 1 | 1 | 1 | 1 | Yes | IVB |
16. | M | + | 5.61 | 41 | T2 | N1a | 0 | 1 | 1 | 0 | No | I |
17. | F | - | 9.86 | 62 | T3a | N1b | 0 | 0 | 0 | 0 | No | II |
18. | F | + | 15 | 59 | T2 | N0 | 1 | 0 | 0 | 1 | No | IVB |
19. | M | - | 5.25 | 65 | T3a | N0 | 1 | 1 | 1 | 0 | Yes | IVB |
20. | F | + | 2.5 | 74 | T1b | N0 | 1 | 0 | 0 | 0 | Yes | IVB |
Parameter | SUV | Age | T | N | M | L | V | R | Stage | Tg | Anti-Tg | EET |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Student t-test (P) | 0.74 | 0.55 | 0.25 | 0.55 | 0.91 | 0.82 | 0.28 | 0.52 | 0.73 | 0.93 | 0.84 | 0.61 |
Variable | Correlation Coefficient | P | Interpretation |
---|---|---|---|
SUV | 0.080 | 0.743 | Low-intensity positive correlation, statistically insignificant |
Age | 0.148 | 0.543 | Low-intensity positive correlation, statistically insignificant |
T | 0.270 | 0.262 | Low-intensity positive correlation, statistically insignificant |
N | –0.145 | 0.552 | Low-intensity negative correlation, statistically insignificant |
M | –0.027 | 0.911 | Low-intensity negative correlation, statistically insignificant |
L | –0.055 | 0.821 | Low-intensity negative correlation, statistically insignificant |
V | –0.258 | 0.285 | Low-intensity negative correlation, statistically insignificant |
R | 0.155 | 0524 | Low-intensity positive correlation, statistically insignificant |
EET | –0.121 | 0.619 | Low-intensity negative correlation, statistically insignificant |
Stage | 0.082 | 0.737 | Low-intensity positive correlation, statistically insignificant |
Tg | 0.020 | 0.933 | Low-intensity positive correlation, statistically insignificant |
Anti-Tg | –0.049 | 0.839 | Low-intensity negative correlation, statistically insignificant |
Variable | Correlation Coefficient | p Value | Interpretation |
---|---|---|---|
SUV | 0.367 | 0.122 | Low-intensity positive correlation, statistically insignificant |
BRAF V600E | 0.082 | 0.737 | Low-intensity positive correlation, statistically insignificant |
Age | 0.653 | 0.002 | Positive medium-intensity, statistically significant correlation |
T | −0.147 | 0.547 | Low-intensity negative correlation, statistically insignificant |
N | −0.307 | 0.200 | Low-intensity negative correlation, statistically insignificant |
M | 0.806 | 0.001 | Positive correlation of strong intensity, statistically significant |
L | −0.015 | 0.95 | Low-intensity negative correlation, statistically insignificant |
V | 0.145 | 0.551 | Low-intensity positive correlation, statistically insignificant |
A | 0.180 | 0.460 | Low-intensity positive correlation, statistically insignificant |
EET | −0.007 | 0.977 | Low-intensity negative correlation, statistically insignificant |
Tg | 0.131 | 0.592 | Low-intensity positive correlation, statistically insignificant |
Anti-Tg | 0.115 | 0.639 | Low-intensity positive correlation, statistically insignificant |
Variable | Correlation Coefficient | p | Interpretation |
---|---|---|---|
Age | 0.251 | 0.483 | Low-intensity positive correlation, statistically insignificant |
T | 0.128 | 0.722 | Low-intensity positive correlation, statistically insignificant |
N | 0.277 | 0.437 | Low-intensity positive correlation, statistically insignificant |
M | −0.017 | 0.96 | Low-intensity negative correlation, statistically insignificant |
L | 0.566 | 0.087 | Positive medium-intensity, statistically insignificant correlation |
V | 0.482 | 0.157 | Low-intensity positive correlation, statistically insignificant |
R | 0.666 | 0.035 | Positive medium-intensity, statistically significant correlation |
EET | −0.095 | 0.793 | Low-intensity negative correlation, statistically insignificant |
Stage | 0.316 | 0.372 | Low-intensity positive correlation, statistically insignificant |
Tg | 0.025 | 0.943 | Low-intensity positive correlation, statistically insignificant |
Anti-Tg | −0.300 | 0.399 | Low-intensity negative correlation, statistically insignificant |
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Piciu, A.; Larg, M.-I.; Piciu, D. Correlation between F18-FDG PET/CT Imaging and BRAF V600E Genetic Mutation for the Early Assessment of Treatment Response in Papillary Thyroid Cancers. J. Pers. Med. 2020, 10, 52. https://doi.org/10.3390/jpm10020052
Piciu A, Larg M-I, Piciu D. Correlation between F18-FDG PET/CT Imaging and BRAF V600E Genetic Mutation for the Early Assessment of Treatment Response in Papillary Thyroid Cancers. Journal of Personalized Medicine. 2020; 10(2):52. https://doi.org/10.3390/jpm10020052
Chicago/Turabian StylePiciu, Andra, Maria-Iulia Larg, and Doina Piciu. 2020. "Correlation between F18-FDG PET/CT Imaging and BRAF V600E Genetic Mutation for the Early Assessment of Treatment Response in Papillary Thyroid Cancers" Journal of Personalized Medicine 10, no. 2: 52. https://doi.org/10.3390/jpm10020052