Copyright
©The Author(s) 2024.
World J Gastrointest Oncol. May 15, 2024; 16(5): 1849-1860
Published online May 15, 2024. doi: 10.4251/wjgo.v16.i5.1849
Published online May 15, 2024. doi: 10.4251/wjgo.v16.i5.1849
Table 1 Demographics of training and validation set
Characteristic | All patients | Training set | Validation set | P value |
n = 144 | n = 100 | n = 44 | ||
Age in yr | 59 ± 10 | 59 ± 9 | 60 ± 10 | 0.514 |
Sex | 0.805 | |||
Male | 97 (67.4) | 68 (68.0) | 29 (65.9) | |
Female | 47 (32.6) | 32 (32.0) | 15 (34.1) | |
CEA in ng/mL1 | 4.0 (2.4, 7.8) | 3.8 (2.3, 9.3) | 0.787 | |
Location | 0.165 | |||
Upper | 31 (21.5) | 22 (22.0) | 9 (20.5) | |
Middle | 66 (45.8) | 41 (41.0) | 25 (56.8) | |
Lower | 47 (32.6) | 37 (37.0) | 10 (22.7) | |
Surgical approach | 0.489 | |||
Dixon | 120 (83.3) | 82 (82.0) | 38 (86.4) | |
Miles | 21 (14.6) | 15 (15.0) | 6 (13.6) | |
Hartman | 3 (2.1) | 3 (3.0) | 0 (0.0) | |
Surgical specimen histological type | 0.877 | |||
Ulcerative | 96 (66.7) | 68 (68.0) | 28 (63.6) | |
Infiltrative | 6 (4.2) | 4 (4.0) | 2 (4.5) | |
Nodular | 42 (29.2) | 28 (28.0) | 14 (31.8) | |
Differentiation | 0.689 | |||
Well | 8 (5.6) | 5 (5.0) | 3 (6.8) | |
Moderate | 86 (59.7) | 62 (62.0) | 24 (54.5) | |
Poor | 50 (34.7) | 33 (33.0) | 17 (38.6) | |
Pathological T stage | 0.579 | |||
T1 | 7 (4.9) | 4 (4.0) | 3 (6.8) | |
T2 | 39 (27.1) | 29 (29.0) | 10 (22.7) | |
T3 | 84 (58.3) | 59 (59.0) | 25 (56.8) | |
T4 | 14 (9.7) | 8 (8.0) | 6 (13.6) | |
Pathological N status | 0.293 | |||
Positive | 53 (36.8) | 34 (34.0) | 19 (43.2) | |
Negative | 91 (63.2) | 66 (66.0) | 25 (56.8) |
Table 2 Baseline characteristics of lymph nodes in the training and validation sets
Features | Training set | Validation set | ||||
NLNM, n = 111 | LNM, n = 78 | P value | NLNM, n = 47 | LNM, n = 34 | P value | |
Size | ||||||
Short axis1 in mm | 6.10 (5.40, 7.20) | 7.80 (6.60, 9.00) | < 0.001 | 5.70 (5.10, 7.40) | 7.25 (6.57, 8.67) | < 0.001 |
Long-axis in mm | 7.63 ± 1.72 | 9.13 ± 1.94 | < 0.001 | 7.55 ± 1.79 | 8.67 ± 1.43 | 0.004 |
Shape | 0.105 | 0.185 | ||||
Non-round | 82 (73.88) | 29 (37.17) | 31 (65.95) | 27 (79.41) | ||
Round | 29 (26.12) | 49 (62.83) | 16 (34.04) | 7 (20.59) | ||
Margin | < 0.001 | 0.001 | ||||
Clear | 55 (49.54) | 13 (16.67) | 24 (51.00) | 4 (14.70) | ||
Unclear | 56 (50.46) | 65 (83.33) | 23 (49.00) | 30 (85.30) | ||
T2WI heterogeneous signal | < 0.001 | 0.029 | ||||
Absent | 63 (56.76) | 17 (21.79) | 25 (53.19) | 5 (14.71) | ||
Present | 48 (43.24) | 61 (78.21) | ||||
Patterns of enhancement | < 0.001 | < 0.001 | ||||
Homogeneous | 65 (58.55) | 8 (10.26) | 32 (68.08) | 8 (23.52) | ||
Heterogeneous | 46 (41.45) | 70 (89.74) | 15 (31.92) | 26 (76.48) | ||
Radiomics score | -1.28 ± 1.28 | 0.62 ± 1.41 | < 0.001 | -1.29 ± 1.27 | 0.60 ± 1.60 | < 0.001 |
Table 3 Risk factors of lymph node metastasis in lymph nodes
Intercept and variable | Conventional MRI model | Nomogram model | ||||
Coefficient | Odds ratio (95%CI) | P value | Coefficient | Odds ratio (95%CI) | P value | |
Intercept | -6.429 | 0.002 (0.001, 0.012) | < 0.001 | -4.270 | 0.014 (0.001, 0.113) | < 0.001 |
Short axis | 0.478 | 1.612 (0.962, 2.745) | 0.072 | 0.088 | 1.092 (0.650, 1.845) | 0.739 |
Long-axis | 0.009 | 1.010 (0.679, 1.520) | 0.963 | 0.178 | 1.194 (0.794, 1.806) | 0.394 |
Margin | 1.431 | 4.184 (1.831, 10.105) | 0.001 | 1.278 | 3.588 (1.592, 8.443) | 0.003 |
T2WI heterogeneous signal | 0.309 | 1.362 (0.586, 3.120) | 0.467 | 0.556 | 1.744 (0.793, 3.856) | 0.166 |
Patterns of enhancement | 2.042 | 7.709 (3.200, 20.561) | < 0.001 | 1.477 | 4.380 (2.004, 9.983) | < 0.001 |
Radiomics score | NA | NA | NA | 0.839 | 2.314 (1.795, 3.086) | < 0.001 |
Table 4 Diagnostic performance of the conventional magnetic resonance imaging model, radiomics model, and nomogram
Data set | Model | AUC (95%CI) | Sensitivity, % | Specificity, % | Accuracy, % |
Training cohort | Conventional MRI model | 0.82 (0.76, 0.87) | 75.0 | 80.0 | 77.8 |
T1WI radiomics model | 0.83 (0.79, 0.87) | 59.5 | 82.6 | 73.5 | |
T2WI radiomics model | 0.85 (0.79, 0.91) | 63.1 | 93.0 | 79.0 | |
T1WI & T2WI Radiomics model | 0.89 (0.84, 0.93) | 74.3 | 86.1 | 81.5 | |
Nomogram model | 0.92 (0.84, 0.99) | 72.2 | 91.1 | 82.8 | |
Validation cohort | Conventional MRI model | 0.80 (0.76, 0.83) | 71.0 | 78.8 | 75.7 |
T1WI radiomics model | 0.81 (0.75, 0.86) | 60.5 | 83.7 | 72.8 | |
T2WI radiomics model | 0.84 (0.80, 0.88) | 62.2 | 87.0 | 77.2 | |
T1WI & T2WI Radiomics model | 0.86 (0.79, 0.92) | 65.8 | 90.7 | 79.0 | |
Nomogram model | 0.91 (0.81, 0.96) | 81.6 | 86.7 | 84.7 |
- Citation: Ye YX, Yang L, Kang Z, Wang MQ, Xie XD, Lou KX, Bao J, Du M, Li ZX. Magnetic resonance imaging-based lymph node radiomics for predicting the metastasis of evaluable lymph nodes in rectal cancer. World J Gastrointest Oncol 2024; 16(5): 1849-1860
- URL: https://www.wjgnet.com/1948-5204/full/v16/i5/1849.htm
- DOI: https://dx.doi.org/10.4251/wjgo.v16.i5.1849