Table 1.
Artificial intelligence-based computer-aided detection and diagnosis application areas in pediatric radiology and their diagnostic performances.
| Author, Year and Country | Modality | Diagnosis | Diagnostic Performance | ||||||
|---|---|---|---|---|---|---|---|---|---|
| AUC | Sensitivity | Specificity | PPV | NPV | Accuracy | F1 Score | |||
| Brain Imaging | |||||||||
| Dou et al. (2022)—China [30] | MRI | Bipolar disorder | 0.830 | 0.909 | 0.769 | NR | NR | 0.854 | NR |
| Kuttala et al. (2022)—Australia, India & United Arab Emirates [31] | MRI | ADHD and ASD | 0.850 (ADHA); 0.910 (ASD) | NR | NR | NR | NR | 0.854 (ADHA); 0.978 (ASD) | NR |
| Li et al. (2020)—China [32] | MRI | Posterior fossa tumors | 0.865 | 0.929 | 0.800 | NR | NR | 0.878 | NR |
| Peruzzo et al. (2016)—Italy [33] | MRI | Malformations of corpus callosum | 0.953 | 0.923 | 0.904 | 0.906 | NR | 0.914 | NR |
| Prince et al. (2020)—USA [34] | CT & MRI | ACP | 0.978 | NR | NR | NR | NR | 0.979 | NR |
| Tan et al. (2013)—USA [35] | MRI | Congenital sensori-neural hearing loss | 0.900 | 0.890 | 0.860 | NR | NR | 0.870 | NR |
| Xiao et al. (2019)—China [36] | MRI | ASD | NR | 0.980 | 0.936 | 0.959 | 0.971 | 0.963 | NR |
| Zahia et al. (2020)—Spain [37] | MRI | Dyslexia | NR | 0.750 | 0.714 | 0.600 | NR | 0.727 | 0.670 |
| Zhou et al. (2021)—China [38] | MRI | ADHD | 0.698 | 0.609 | 0.676 | NR | NR | 0.643 | 0.626 |
| Cardiac Imaging | |||||||||
| Lee et al. (2022)—South Korea [39] | US | Kawasaki disease | NR | 0.841 | 0.585 | 0.811 | 0.633 | 0.759 | 0.826 |
| Musculoskeletal Imaging | |||||||||
| Petibon et al. (2021)—Canada, Israel and USA [40] | SPECT | Low back pain | 0.830 | NR | NR | NR | NR | NR | NR |
| Sezer and Sezer (2020)—France and Turkey [41] | US | DDH | NR | 0.962 | 0.980 | NR | NR | 0.977 | NR |
| Respiratory Imaging | |||||||||
| Behzadi—Khormouji et al. (2020)—Iran and USA [42] | X-ray | Pulmonary consolidation | 0.995 | 0.987 | 0.864 | NR | NR | 0.945 | NR |
| Bodapati and Rohith (2022)—India [43] | X-ray | Pneumonia | 0.939 | NR | NR | NR | NR | 0.948 | 0.959 |
| Helm et al. (2009)—Canada, UK and USA [44] | CT | Pulmonary nodules | NR | 0.420 | 1.000 | 1.000 | 0.260 | NR | NR |
| Jiang and Chen (2022)-China [45] | X-ray | Pneumonia | NR | 0.894 | NR | 0.918 | NR | 0.912 | 0.903 |
| Liang and Zheng (2020)-China [46] | X-ray | Pneumonia | 0.953 | 0.967 | NR | 0.891 | NR | 0.905 | 0.927 |
| Mahomed et al. (2020)-Netherlands and South Africa [47] | X-ray | Primary-endpoint pneumonia | 0.850 | 0.760 | 0.800 | NR | NR | NR | NR |
| Shouman et al. (2022)-Egypt and Saudi Arabia [48] | X-ray | Bacterial and viral pneumonia | 0.999 | 0.987 | 0.987 | 0.979 | NR | 0.986 | 0.983 |
| Silva et al. (2022)-Brazil [49] | X-ray | Pneumonia | NR | 0.945 | NR | 0.957 | NR | NR | 0.951 |
| Vrbančič and Podgorelec (2022)-Slovenia [50] | X-ray | Pneumonia | 0.952 | 0.976 | 0.927 | 0.973 | NR | 0.963 | 0.974 |
| Urologic Imaging | |||||||||
| Guan et al. (2022)-China [51] | US | Hydronephrosis | NR | NR | NR | NR | NR | 0.891 | 0.895 |
| Zheng et al. (2019)-China and USA [52] | US | CAKUT | 0.920 | 0.86 | 0.880 | NR | NR | 0.870 | NR |
ACP, adamantinomatous craniopharyngioma; ADHD, attention deficit hyperactivity disorder; ASD, autism spectrum disorder; AUC, area under receiver operating characteristic curve; CAKUT, congenital abnormalities of kidney and urinary tract; CT, computed tomography; DDH, developmental dysplasia of hip; MRI, magnetic resonance imaging; NPV, negative predictive value; NR, not reported; PPV, positive predictive value; SPECT, single-photon emission computed tomography; UK, United Kingdom; US, ultrasound; USA, United States of America.