Evaluation of Matrix Metalloproteases by Artificial Intelligence Techniques in Negative Biopsies as New Diagnostic Strategy in Prostate Cancer
Abstract
:1. Introduction
2. Results
2.1. Comparative Study of the Expression of Factors among Different Benign Tissues Accuracy
2.2. Evolutionary Changes in Paired Prostate Tissues from Benign Tissues to Cancer Diagnosis
3. Discussion
4. Materials and Methods
4.1. Patients
4.2. Immunohistochemical Analysis
4.3. Description of Data Sets
- (a)
- Training dataset: the data were used to train the algorithm to obtain the relevant and coherent knowledge and information capable of discriminating the input breaking down data (MMP-2, -9, -11, -13, and TIMP-3 expression);
- (b)
- Test dataset: the data were used to determine whether the behavior and knowledge provided by the intelligent system are adequate, through the corresponding evaluation by the degree of success or accuracy, and thus verify the effectiveness of the said algorithm.
4.4. Data Analysis and Intelligent Algorithms: Description and Evaluation
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Epithelial Cells | SVM | LR | DeepL | xbgoost | FURIA |
---|---|---|---|---|---|
C1 vs. C5 | 97.2% | 95.9% | 71.6% | 95.9% | 97.2% |
C2 vs. C5 | 95.9% | 91.8% | 78.3% | 93.2% | 96.0% |
C1 vs. C6 | 95.7% | 93.6% | 72.3% | 95.7% | 97.6% |
C2 vs. C6 | 93.6% | 87.2% | 61.7% | 82.9% | 98.0% |
Fibroblasts | SVM | LR | DeepL | xbgoost | FURIA |
---|---|---|---|---|---|
C1 vs. C5 | 67.5% | 71.6% | 62.1% | 78.3% | 84.2% |
C2 vs. C5 | 83.7% | 77.0% | 64.8% | 85.1% | 87.8% |
C1 vs. C6 | 78.7% | 80.8% | 57.4% | 85.1% | 88.5% |
C2 vs. C6 | 78.7% | 68.0% | 55.3% | 74.4% | 81.7% |
Benign prostate biopsy before the diagnosis of PCa Class 1: Zone without future cancer development (C1) Class 2: Zone with future tumor (C2) |
Positive biopsy: PCa Class 3: Non-tumor area from prostatectomy (C3) Class 4: Tumor area from prostatectomy (C4) |
Class 5: Benign prostatic hyperplasia (BPH) (C5) |
Class 6: High-grade prostate intraepithelial neoplasia (HGPIN) (C6) |
Prediction | |||
---|---|---|---|
Positives | Negatives | ||
True | Positives | VN | FN |
Negatives | FP | VN |
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Eiro, N.; Medina, A.; Gonzalez, L.O.; Fraile, M.; Palacios, A.; Escaf, S.; Fernández-Gómez, J.M.; Vizoso, F.J. Evaluation of Matrix Metalloproteases by Artificial Intelligence Techniques in Negative Biopsies as New Diagnostic Strategy in Prostate Cancer. Int. J. Mol. Sci. 2023, 24, 7022. https://doi.org/10.3390/ijms24087022
Eiro N, Medina A, Gonzalez LO, Fraile M, Palacios A, Escaf S, Fernández-Gómez JM, Vizoso FJ. Evaluation of Matrix Metalloproteases by Artificial Intelligence Techniques in Negative Biopsies as New Diagnostic Strategy in Prostate Cancer. International Journal of Molecular Sciences. 2023; 24(8):7022. https://doi.org/10.3390/ijms24087022
Chicago/Turabian StyleEiro, Noemi, Antonio Medina, Luis O. Gonzalez, Maria Fraile, Ana Palacios, Safwan Escaf, Jesús M. Fernández-Gómez, and Francisco J. Vizoso. 2023. "Evaluation of Matrix Metalloproteases by Artificial Intelligence Techniques in Negative Biopsies as New Diagnostic Strategy in Prostate Cancer" International Journal of Molecular Sciences 24, no. 8: 7022. https://doi.org/10.3390/ijms24087022