Technological Frontiers in Brain Cancer: A Systematic Review and Meta-Analysis of Hyperspectral Imaging in Computer-Aided Diagnosis Systems
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Selection Criteria
2.2. QUADAS-2 Results
3. Results
3.1. Clinical Features Observed in the Studies
3.2. Meta-Analysis of the Studies
3.3. Subgroup Meta-Analysis
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Year | Author | Application | Spectral Range (nm) |
---|---|---|---|
2012 [34] | Hamed Akbari et al. | Prostate cancer | 500 to 950 nm |
2017 [32] | Guolan Lu et al. | Head and neck cancer | 450 to 900 nm |
2020 [89] | Francesca Manni et al. | Colon cancer | up to 1700 nm |
2022 [90] | Tsung-Jung Tsai at al. | Esophageal cancer | 415 and 540 nm |
2015 [91] | Atsushi Goto et al. | Gastric cancer | 1000 to 2500 nm |
2021 [92] | Xuehu Wang et al. | Liver cancer | 400–1000 nm |
2020 [93] | Ibrahim H et al. | Breast cancer | 400–700 nm |
2023 [94] | Riheng Chen et al. | Blood cancer | 400–1000 nm |
Study | Risk of Bias | Applicability Concerns | |||||
---|---|---|---|---|---|---|---|
Patient Selection | Index Test | Reference Standard | Flow and Timing | Patient Selection | Index Test | Reference Standard | |
Beatriz Martinez et al., 2019 [97] | ? | ? | ? | ||||
Gemma Urbanos et al., 2021 [98] | ? | ? | |||||
Samuel Ortega et al., 2018 [99] | ? | ||||||
Francesca Manni et al., 2020 [100] | ? | ? | ? | ||||
Samuel Ortega et al., 2020 [101] | ? | ? | ? | ||||
Himar Fabelo et al., 2018 [32] | ? | ? | ? | ? | |||
Himar Fabelo et al., 2019 [102] | ? | ? | ? | ? | ? |
Author Year | Nationality | Method | Band | Vivo | Index Number | Dataset | Accuracy (%) | Sensitivity (%) | Specificity (%) | AUC (%) |
---|---|---|---|---|---|---|---|---|---|---|
Beatriz Martinez et al., 2019 [97] | Western | SVM band L1 | VNIR | In Vivo | 1 | 26 | 77.9 | 52.7 | 94.6 | N/A |
SVM band L2 | 2 | 77 | 57 | 91.2 | ||||||
SVM band L3 | 3 | 53.8 | 57.6 | 70.3 | ||||||
Gemma Urbanos et al., 2021 [98] | Western | SVM | VNIR | In Vitro | 4 | 13 | 76.5 | 26 | 91 | N/A |
RF | 5 | 82.5 | 48.5 | 99 | ||||||
CNN | 6 | 77 | 47.5 | 99 | ||||||
SAMUEL ORTEGA et al., 2018 [99] | Western | SVM | VNIR | In Vivo | 7 | 21 biopsies | 75.53 | 75.69 | 70.97 | N/A |
ANN | 8 | 78.02 | 75.44 | 77.03 | ||||||
RF | 9 | 69.13 | 72.94 | 79.33 | ||||||
Francesca Manni et al., 2020 [100] | Western | 3D–2D CNN | VNIR | In Vivo | 10 | 26 | 80 | 68 | 98 | 70 |
3D–2D CNN + SVM | 11 | 75 | 42 | 98 | 76 | |||||
SVM | 12 | 76 | 43 | 98 | 70 | |||||
2DCNN | 13 | 72 | 14 | 97 | 71 | |||||
1DDNN | 14 | 78 | 19 | 97 | 89 | |||||
SAMUEL ORTEGA et al., 2020 [101] | Western | CNN HIS | VNIR | In Vivo | 15 | 13 biopsies | 85 | 88 | 77 | 87 |
CNN RGB | 16 | 80 | 81 | 68 | 84 | |||||
Himar Fabelo et al., 2018 [32] | Western | SVM | VNIR | In Vivo | 17 | 5 | 99.72 | 99.62 | 99.91 | N/A |
Himar Fabelo et al., 2019 [102] | Western | 1D-DNN | VNIR | In Vivo | 18 | 26 | 94 | 88 | 100 | 99 |
2D-CNN | 19 | 88 | 76 | 100 | 97 | |||||
SVM RBF Opt. | 20 | 84 | 68 | 100 | 97 | |||||
SVM RBF Def. | 21 | 73 | 58 | 88 | 86 | |||||
SVM Linear Opt. | 22 | 77 | 54 | 100 | 99 | |||||
SVM Linear Def | 23 | 68 | 49 | 88 | 86 |
Subgroup | Number of Studies | Accuracy (%) | Sensitivity (%) | Specificity (%) | AUC (%) |
---|---|---|---|---|---|
Average meta-analysis of all studies | 8 | 78.96 | 62.43 | 90.05 | 81.06 |
Vivo | |||||
In vivo | 6 | 78.72 | 56.84 | 92.70 | 85.46 |
In vitro | 2 | 79.93 | 84.81 | 79.46 | 93.05 |
Machine Learning | |||||
SVM | 11 | 76.22 | 58.23 | 90.18 | 87.6 |
CNN | 6 | 80.34 | 62.41 | 89.84 | 81.8 |
DNN | 2 | 86 | 53.5 | 98.5 | 94 |
RF | 2 | 75.81 | 60.72 | 89.16 | N/A |
ANN | 1 | 78.02 | 75.44 | 77.03 | N/A |
CNN + SVM | 1 | 75 | 42 | 98 | 76 |
Cancer Type | |||||
GBM | 6 | 78.05 | 61.94 | 89.61 | 85.46 |
Gliomas | 1 | 78.67 | 40.67 | 96.34 | N/A |
Meningiomas | 1 | 88.5 | 100 | 85 | 93.05 |
Publishing Date | |||||
2018–2020 | 6 | 78.05 | 61.94 | 89.61 | 85.46 |
2021–2024 | 2 | 82.6 | 64.4 | 91.8 | 93.05 |
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Leung, J.-H.; Karmakar, R.; Mukundan, A.; Lin, W.-S.; Anwar, F.; Wang, H.-C. Technological Frontiers in Brain Cancer: A Systematic Review and Meta-Analysis of Hyperspectral Imaging in Computer-Aided Diagnosis Systems. Diagnostics 2024, 14, 1888. https://doi.org/10.3390/diagnostics14171888
Leung J-H, Karmakar R, Mukundan A, Lin W-S, Anwar F, Wang H-C. Technological Frontiers in Brain Cancer: A Systematic Review and Meta-Analysis of Hyperspectral Imaging in Computer-Aided Diagnosis Systems. Diagnostics. 2024; 14(17):1888. https://doi.org/10.3390/diagnostics14171888
Chicago/Turabian StyleLeung, Joseph-Hang, Riya Karmakar, Arvind Mukundan, Wen-Shou Lin, Fathima Anwar, and Hsiang-Chen Wang. 2024. "Technological Frontiers in Brain Cancer: A Systematic Review and Meta-Analysis of Hyperspectral Imaging in Computer-Aided Diagnosis Systems" Diagnostics 14, no. 17: 1888. https://doi.org/10.3390/diagnostics14171888