An Interpretable Radiomics Model Based on Two-Dimensional Shear Wave Elastography for Predicting Symptomatic Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma
Abstract
:Simple Summary
Abstract
1. Introduction
2. Materials and Methods
2.1. Patients
2.2. Two-Dimensional SWE Data Acquisition
2.3. Clinical Data Collection
2.4. Diagnosis and Staging of Symptomatic PHLF
2.5. Construction of Radiomics Models
- (1)
- Image preprocessing:
- (2)
- The radiomics model based on 2D-SWE images:
- (3)
- The clinical–radiomics model based on 2D-SWE images and clinical data:
2.6. Shapley Additive exPlanations
2.7. Statistical Analysis
3. Results
3.1. Baseline Characteristics
3.2. Performance of the Clinical Model
3.3. Performance of the Radiomics Model and the Clinical–Radiomics Model in Five-Fold Cross-Validation
3.4. Performance of the Radiomics Model and the Clinical–Radiomics Model in the Test Set
3.5. Shapley Additive exPlanations
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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Characteristic | All Patients (n = 345) | Training Cohort (n = 265) | Test Cohort (n = 80) | p-Value |
---|---|---|---|---|
Age (year) | 55.0 (47.0–64.0) | 55.0 (47.0–64.0) | 54.0 (49.0–66.8) | 0.354 |
Sex (male/female) | 305/40 | 238/27 | 67/13 | 0.138 |
Underlying liver disease (HBV/HCV/coinfection of HBV and HCV/unknown) | 324/7/6/8 | 249/5/5/6 | 75/2/1/2 | 0.965 |
TBIL (umol/L) | 13.8 (10.7–17.3) | 13.6 (10.6–16.9) | 15.0 (11.5–17.9) | 0.081 |
ALB (g/L) | 38.3 (36.2–41.0) | 38.3 (36.2–41.0) | 38.8 (36.2–41.2) | 0.942 |
CREA (umol/L) | 79.0 (68.0–87.0) | 79.0 (68.0–87.5) | 80.0 (68.3–87.0) | 0.940 |
ALT (U/L) | 31.0 (21.0–43.5) | 32.0 (20.0–43.0) | 31.0 (22.0–52.8) | 0.805 |
AST (U/L) | 35.0 (25.0–50.0) | 35.0 (26.0–50.0) | 36.0 (23.0–50.7) | 0.812 |
GGT (U/L) | 55.0 (34.0–98.5) | 59.0 (36.0–103.0) | 50.0 (30.3–85.8) | 0.055 |
PT (s) | 11.9 (11.3–12.6) | 11.8 (11.2–12.4) | 12.2 (11.7–12.8) | 0.002 |
INR | 1.02 (0.97–1.07) | 1.01 (0.96–1.06) | 1.05 (1.00–1.09) | <0.001 |
AFP (U/L) | 23.1 (4.4–516.1) | 21.2 (4.5–527.4) | 49.6 (4.1–476.3) | 0.829 |
ALBI | −2.52 [(−2.72)–(−2.34)] | −2.53 [−(2.73)–(−2.34)] | −2.54 [−(2.67)–(−2.33)] | 0.863 |
ALBI grade (1/2) | 137/208 | 104/161 | 33/47 | 0.748 |
Child–Pugh score (5/6/7) | 276/53/16 | 211/39/15 | 65/14/1 | 0.234 |
Child–Pugh grade (A/B) | 329/16 | 250/15 | 79/1 | 0.100 |
MELD | 4.8 (2.9–6.3) | 4.6 (2.6–6.2) | 5.4 (3.9–7.3) | 0.012 |
Cirrhosis (yes/no) | 120/225 | 90/175 | 30/50 | 0.560 |
CSPH (yes/no) | 39/306 | 29/236 | 10/70 | 0.700 |
Splenomegaly (yes/no) | 101/244 | 83/182 | 18/62 | 0.129 |
Ascite (yes/no) | 22/323 | 19/246 | 3/77 | 0.273 |
Tumor size (cm) | 5.4 (3.5–8.3) | 5.7 (3.6–8.4) | 4.5 (3.0–7.5) | 0.107 |
BCLC stage (0/A/B/C) | 19/222/62/42 | 14/163/49/39 | 5/59/13/3 | 0.051 |
TLV (mL) | 1242.4 (1083.4–1528.2) | 1242.4 (1086.1–1531.2) | 1230.6 (1070.5–1526.0) | 0.707 |
RLV (mL) | 428.0 (234.7–687.5) | 433.1 (234.7–704.9) | 366.1 (226.1–633.3) | 0.229 |
LRV | 788.6 (643.5–963.1) | 788.6 (631.6–957.7) | 787.2 (689.9–1003.6) | 0.465 |
LRV ratio | 0.67 (0.50–0.80) | 0.66 (0.48–0.79) | 0.69 (0.54–0.80) | 0.186 |
Symptomatic PHLF (yes/no) | 107/238 | 80/185 | 27/53 | 0.546 |
Variables | Univariate Analysis | p-Value | Multivariate Analysis | p-Value |
---|---|---|---|---|
OR (95% CI) | OR (95% CI) | |||
Sex, female vs. male | 0.791 (0.320–1.953) | 0.791 | − | − |
Age (years) | 1.003 (0.981–1.025) | 0.811 | − | − |
TBIL (umol/L) | 1.033 (0.998–1.069) | 0.062 | − | − |
ALB (g/L) | 0.900 (0.838–0.967) | 0.004 | − | − |
CREA (umol/L) | 0.997 (0.988–1.006) | 0.562 | − | − |
ALT (U/L) | 1.001 (0.998–1.005) | 0.446 | − | − |
AST (U/L) | 1.002 (0.999–1.006) | 0.234 | − | − |
GGT (U/L) | 1.003 (1.000–1.005) | 0.024 | − | − |
PT (s) | 1.343 (1.058–1.706) | 0.015 | − | − |
INR | 2461.350 (70.906–85,440.280) | <0.001 | 2424.484 (49.342–119,130.427) | <0.001 |
AFP (U/L) | 1.000(1.000–1.000) | 0.244 | − | − |
ALBI score | 4.533 (1.947–10.557) | <0.001 | − | − |
Child–Pugh score | 2.031 (1.292–3.193) | 0.002 | − | − |
Child–Pugh grade, B vs. A | 3.782 (1.299–11.013) | 0.015 | − | − |
MELD | 1.115(1.018–1.222) | 0.019 | − | − |
Cirrhosis, yes vs. no | 2.499 (1.450–4.307) | 0.001 | − | − |
CSPH, yes vs. no | 3.308 (1.507–7.260) | 0.003 | 4.670 (0.001–0.023) | 0.001 |
Splenomegaly, yes vs. no | 1.618 (0.931–2.811) | 0.088 | − | − |
Ascites, yes vs. no | 2.218 (0.865–5.689) | 0.097 | − | − |
Tumor size (cm) | 1.177 (1.090–1.272) | <0.001 | − | − |
BCLC stage | 1.536 (1.113–2.118) | 0.009 | − | − |
TLV (mL) | 1.001 (1.000–1.002) | 0.001 | − | − |
RLV (mL) | 1.002 (1.001–1.003) | <0.001 | − | − |
LRV (mL) | 0.997 (0.996–0.998) | <0.001 | − | − |
LRV ratio | 0.009 (0.002–0.039) | <0.001 | 0.004 (0.001–0.023) | <0.001 |
Model | AUC (CI) | Accuracy ±STD | Sensitivity ±STD | Specificity ±STD | PPV ±STD | NPV ±STD |
---|---|---|---|---|---|---|
Radiomics | 0.746 (0.681–0.811) | 0.698 ± 0.054 | 0.725 ± 0.064 | 0.686 ± 0.098 | 0.511 ± 0.060 | 0.853 ± 0.019 |
Clinical | 0.809 (0.715–0.902) | 0.739 ± 0.051 | 0.713 ± 0.170 | 0.751 ± 0.035 | 0.549 ± 0.057 | 0.865 ± 0.078 |
Clinical–radiomics | 0.867 (0.787–0.947) | 0.800 ± 0.081 | 0.800 ± 0.0.073 | 0.800 ± 0.103 | 0.652 ± 0.120 | 0.901 ± 0.035 |
Model | AUC | Accuracy | Sensitivity | Specificity | PPV | NPV |
---|---|---|---|---|---|---|
Radiomics | 0.784 | 0.725 | 0.660 | 0.754 | 0.581 | 0.816 |
Clinical | 0.684 | 0.650 | 0.550 | 0.698 | 0.484 | 0.755 |
Clinical–radiomics | 0.822 | 0.750 | 0.704 | 0.773 | 0.612 | 0.836 |
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Zhong, X.; Salahuddin, Z.; Chen, Y.; Woodruff, H.C.; Long, H.; Peng, J.; Xie, X.; Lin, M.; Lambin, P. An Interpretable Radiomics Model Based on Two-Dimensional Shear Wave Elastography for Predicting Symptomatic Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma. Cancers 2023, 15, 5303. https://doi.org/10.3390/cancers15215303
Zhong X, Salahuddin Z, Chen Y, Woodruff HC, Long H, Peng J, Xie X, Lin M, Lambin P. An Interpretable Radiomics Model Based on Two-Dimensional Shear Wave Elastography for Predicting Symptomatic Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma. Cancers. 2023; 15(21):5303. https://doi.org/10.3390/cancers15215303
Chicago/Turabian StyleZhong, Xian, Zohaib Salahuddin, Yi Chen, Henry C. Woodruff, Haiyi Long, Jianyun Peng, Xiaoyan Xie, Manxia Lin, and Philippe Lambin. 2023. "An Interpretable Radiomics Model Based on Two-Dimensional Shear Wave Elastography for Predicting Symptomatic Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma" Cancers 15, no. 21: 5303. https://doi.org/10.3390/cancers15215303