Radiomic Analysis Based on Magnetic Resonance Imaging for Predicting PD-L2 Expression in Hepatocellular Carcinoma
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Patient
2.2. Immunohistochemistry
2.3. MR Image Acquisition
2.4. Tumour Segmentation and Feature Extraction
2.5. Feature Screening and Model Establishment
2.6. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Sequence | TR/TE (ms) | FA (°) | FOV (mm2) | ST (mm) | Matrix (mm2) |
---|---|---|---|---|---|
T1WI | 4/2 | 12 | 320 × 320–360 × 360 | 2.5 | 260 × 192 |
FS-T2WI | 2609/97 | 110 | 320 × 320–380 × 380 | 6 | 384 × 384 |
DCE-MRI | 4/2 | 12 | 320 × 320–360 × 360 | 5 | 224 × 192 |
Clinical Variables | Total (n = 108) | High PD-L2 Expression (n = 50) | Low PD-L2 Expression (n = 58) | p |
---|---|---|---|---|
Age (years) | 0.105 | |||
≤60 | 69 (64%) | 36 (72%) | 33 (57%) | |
>60 | 39 (36%) | 14 (28%) | 25 (43%) | |
Sex (%) | 0.163 | |||
Male | 94 (87%) | 46 (92%) | 48 (79%) | |
Female | 14 (13%) | 4 (8%) | 10 (21%) | |
AFP (ng/mL) | 0.375 | |||
<20 | 37 (34%) | 18 (36%) | 19 (33%) | |
20–400 | 25 (23%) | 14 (28%) | 11 (19%) | |
≥400 | 46 (43%) | 18 (36%) | 28 (48%) | |
Diameter (cm) | 0.629 | |||
0–5 | 47 (44%) | 23 (46%) | 24 (41%) | |
≥5 | 61 (56%) | 27 (54%) | 34 (59%) | |
Hepatitis B | 0.785 | |||
No | 12 (11%) | 7 (14%) | 5 (9%) | |
Yes | 96 (89%) | 43 (86%) | 53 (91%) | |
Liver cirrhosis | 0.504 | |||
No | 27 (25%) | 14 (28%) | 13 (22%) | |
Yes | 81 (75%) | 36 (72%) | 45 (78%) | |
Portal vein tumour thrombus | 0.664 | |||
No | 82 (76%) | 37 (74%) | 45 (78%) | |
Yes | 26 (24%) | 13 (26%) | 13 (22%) |
Model | AUC of Training Set (95% CI) | AUC of Validation Set (95% CI) | Accuracy | Sensitivity | Specificity | p Value |
---|---|---|---|---|---|---|
FS-T2WI | 0.852 (0.781–0.924) | 0.789 (0.702–0.875) | 73.15% | 66.00% | 79.31% | 0.0051 |
AP | 0.814 (0.734–0.895) | 0.727 (0.632–0.823) | 69.44% | 62.00% | 75.86% | 0.0006 |
PVP | 0.857 (0.789–0.925) | 0.770 (0.682–0.857) | 71.30% | 70.00% | 72.41% | 0.0018 |
Combined | 0.955 (0.921–0.989) | 0.871 (0.803–0.939) | 82.41% | 86.00% | 79.31% | Reference |
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Share and Cite
Tao, Y.-Y.; Shi, Y.; Gong, X.-Q.; Li, L.; Li, Z.-M.; Yang, L.; Zhang, X.-M. Radiomic Analysis Based on Magnetic Resonance Imaging for Predicting PD-L2 Expression in Hepatocellular Carcinoma. Cancers 2023, 15, 365. https://doi.org/10.3390/cancers15020365
Tao Y-Y, Shi Y, Gong X-Q, Li L, Li Z-M, Yang L, Zhang X-M. Radiomic Analysis Based on Magnetic Resonance Imaging for Predicting PD-L2 Expression in Hepatocellular Carcinoma. Cancers. 2023; 15(2):365. https://doi.org/10.3390/cancers15020365
Chicago/Turabian StyleTao, Yun-Yun, Yue Shi, Xue-Qin Gong, Li Li, Zu-Mao Li, Lin Yang, and Xiao-Ming Zhang. 2023. "Radiomic Analysis Based on Magnetic Resonance Imaging for Predicting PD-L2 Expression in Hepatocellular Carcinoma" Cancers 15, no. 2: 365. https://doi.org/10.3390/cancers15020365