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©The Author(s) 2024.
World J Gastroenterol. Apr 28, 2024; 30(16): 2233-2248
Published online Apr 28, 2024. doi: 10.3748/wjg.v30.i16.2233
Published online Apr 28, 2024. doi: 10.3748/wjg.v30.i16.2233
Table 1 Magnetic resonance imaging parameters of each sequence
Scanner | Sequence | Orientation | TR (ms) | TE (ms) | FOV (mm2) | Matrix | Thickness (mm) |
Siemens Aera 1.5T | T2WI | Oblique axial | 4480 | 87 | 190 × 190 | 320 × 320 | 3 |
T1CE | Oblique axial | 7 | 3 | 210 × 210 | 256 × 256 | 3 | |
GE Signa HDxt 1.5T | T2WI | Oblique axial | 4120 | 70 | 180 × 180 | 256 × 192 | 3 |
T1CE | Oblique axial | 6 | 3 | 200 × 200 | 288 × 160 | 3 |
Table 2 Characteristics of patients in the training, internal validation and external validation groups, n (%)
Characteristics | Training group (n = 118) | P value | Internal validation group (n = 52) | P value | External validation group (n = 74) | P value | |||
PNI+ (n = 39) | PNI- (n = 79) | PNI+ (n = 17) | PNI- (n = 35) | PNI+ (n = 25) | PNI- (n = 49) | ||||
Sex | 0.854 | 0.882 | 0.640 | ||||||
Male | 25 (64.1) | 52 (65.8) | 12 (70.6) | 24 (68.6) | 16 (64.0) | 34 (69.4) | |||
Female | 14 (35.9) | 27 (34.2) | 5 (29.4) | 11 (31.4) | 9 (36.0) | 15 (30.6) | |||
Age (yr) | 68 (56.5-73) | 68 (58.5-75) | 0.479 | 66.59 ± 12.57 | 64.17 ± 10.32 | 0.497 | 65.24 ± 11.70 | 66.84 ± 9.85 | 0.562 |
CEA | 0.150 | 0.027 | 0.005 | ||||||
Negative (< 5 ng/mL) | 23 (59.0) | 57 (72.2) | 9 (52.9) | 30 (85.7) | 14 (56.0) | 42 (85.7) | |||
Positive (≥ 5 ng/mL) | 16 (41.0) | 22 (27.8) | 8 (47.1) | 5 (14.3) | 11 (44.0) | 7 (14.3) | |||
CA19-9 | 0.034 | 0.019 | 1.000 | ||||||
Negative (< 30 U/mL) | 30 (76.9) | 72 (91.1) | 12 (70.6) | 34 (97.1) | 23 (92.0) | 46 (93.9) | |||
Positive (≥ 30 U/mL) | 9 (23.1) | 7 (8.9) | 5 (29.4) | 1 (2.9) | 2 (8.0) | 3 (6.1) | |||
DIS | 0.050 | 0.444 | 0.823 | ||||||
High | 24 (61.5) | 31 (39.2) | 9 (52.9) | 15 (42.9) | 12 (48.0) | 22 (44.9) | |||
Mid | 3 (7.7) | 16 (20.3) | 5 (29.4) | 9 (25.7) | 5 (20.0) | 13 (26.5) | |||
Low | 12 (30.8) | 32 (40.5) | 3 (17.6) | 11 (31.4) | 8 (32.0) | 14 (28.6) | |||
mT | 0.211 | 0.885 | 0.314 | ||||||
mT1-2 | 3 (7.7) | 15 (19.0) | 6 (35.3) | 10 (28.6) | 5 (20.0) | 9 (18.4) | |||
mT3 | 24 (61.5) | 47 (59.5) | 8 (47.1) | 18 (51.4) | 14 (56.0) | 32 (65.3) | |||
mT4 | 12 (30.8) | 17 (21.5) | 3 (17.6) | 7 (20.0) | 6 (24.0) | 8 (16.3) | |||
mN | 0.003 | 0.063 | 0.028 | ||||||
mN0 | 5 (12.8) | 27 (34.2) | 3 (17.6) | 18 (51.4) | 6 (24.0) | 19 (38.8) | |||
mN1 | 13 (33.3) | 33 (41.8) | 5 (29.4) | 7 (20.0) | 7 (28.0) | 21 (42.9) | |||
mN2 | 21 (53.8) | 19 (24.1) | 9 (52.9) | 10 (28.6) | 12 (48.0) | 9 (18.4) | |||
cM | 0.070 | 1.000 | 0.064 | ||||||
cM0 | 34 (87.2) | 77 (97.5) | 17 (100.0) | 34 (97.1) | 22 (88.0) | 49 (100.0) | |||
cM1 | 5 (12.8) | 2 (2.5) | 0 (0.0) | 1 (2.9) | 3 (12.0) | 0 (0.0) | |||
cTNM | 1.000 | 1.000 | 1.000 | ||||||
Ⅰ | 1 (2.6) | 29 (36.7) | 0 (0.0) | 16 (45.7) | 0 (0.0) | 18 (36.7) | |||
Ⅱ | 9 (23.1) | 25 (31.6) | 5 (29.4) | 13 (37.1) | 3 (12.0) | 12 (24.5) | |||
Ⅲ | 25 (64.1) | 23 (29.1) | 11 (64.7) | 5 (14.3) | 19 (76.0) | 19 (38.8) | |||
Ⅳ | 4 (10.3) | 2 (2.5) | 1 (5.9) | 1 (2.9) | 3 (12.0) | 0 (0.0) | |||
mCRM | 0.002 | 0.374 | 0.236 | ||||||
Negative | 14 (35.9) | 52 (65.8) | 9 (52.9) | 23 (65.7) | 15 (60.0) | 36 (73.5) | |||
Positive | 25 (64.1) | 27 (34.2) | 8 (47.1) | 12 (34.3) | 10 (40.0) | 13 (26.5) | |||
mEMVI | 0.016 | 0.935 | 0.009 | ||||||
Negative | 15 (38.5) | 49 (62.0) | 10 (58.8) | 21 (60.0) | 10 (40.0) | 35 (71.4) | |||
Positive | 24 (61.5) | 30 (38.0) | 7 (41.2) | 14 (40.0) | 15 (60.0) | 14 (28.6) | |||
Histological grade | 0.000 | 0.920 | 0.894 | ||||||
Well differentiated | 4 (10.3) | 27 (34.2) | 2 (11.8) | 11 (31.4) | 4 (16.0) | 13 (26.5) | |||
Moderately differentiated | 26 (66.7) | 49 (62.0) | 12 (70.6) | 23 (65.7) | 18 (72.0) | 34 (69.4) | |||
Poorly differentiated | 9 (23.1) | 3 (3.8) | 3 (17.6) | 1 (2.9) | 3 (12.0) | 2 (4.1) |
Table 3 Performance of various predictive models in the training, internal validation and external validation groups
Models | Training group | Internal validation group | External validation group |
T2WI | |||
AUC (95%CI) | 0.817 (0.733-0.901) | 0.763 (0.626-0.900) | 0.759 (0.644-0.875) |
Sensitivity | 0.564 | 0.294 | 0.480 |
Specificity | 0.899 | 0.886 | 0.857 |
Positive predictive value | 0.733 | 0.556 | 0.632 |
Negative predictive value | 0.807 | 0.721 | 0.764 |
T1CE | |||
AUC (95%CI) | 0.798 (0.707-0.890) | 0.689 (0.521-0.857) | 0.841 (0.752-0.930) |
Sensitivity | 0.487 | 0.471 | 0.480 |
Specificity | 0.937 | 0.857 | 0.878 |
Positive predictive value | 0.792 | 0.615 | 0.667 |
Negative predictive value | 0.787 | 0.769 | 0.768 |
T2WI + T1CE | |||
AUC (95%CI) | 0.839 (0.757-0.921) | 0.787 (0.650-0.923) | 0.836 (0.735-0.937) |
Sensitivity | 0.641 | 0.529 | 0.560 |
Specificity | 0.899 | 0.914 | 0.939 |
Positive predictive value | 0.758 | 0.750 | 0.824 |
Negative predictive value | 0.835 | 0.800 | 0.807 |
Clinical model | |||
AUC (95%CI) | 0.804 (0.727-0.881) | 0.828 (0.719-0.937) | 0.813 (0.724-0.903) |
Sensitivity | 0.718 | 0.706 | 0.800 |
Specificity | 0.747 | 0.829 | 0.694 |
Positive predictive value | 0.583 | 0.667 | 0.571 |
Negative predictive value | 0.843 | 0.829 | 0.872 |
CR model | |||
AUC (95%CI) | 0.889 (0.824-0.954) | 0.889 (0.803-0.976) | 0.894 (0.814-0.974) |
Sensitivity | 0.692 | 0.647 | 0.760 |
Specificity | 0.924 | 0.886 | 0.899 |
Positive predictive value | 0.818 | 0.733 | 0.792 |
Negative predictive value | 0.859 | 0.838 | 0.880 |
Table 4 Results of univariate and multivariate logistic regression analyses
Variables | Univariate logistic regression | Multivariate logistic regression | ||
OR (95%CI) | P value | OR (95%CI) | P value | |
Gender | 0.927 (0.418-2.098) | 0.854 | NA | NA |
Age | 0.976 (0.944-1.008) | 0.138 | NA | NA |
CEA | 1.802 (0.801-4.045) | 0.152 | NA | NA |
CA19-9 | 3.086 (1.056-9.375) | 0.040a | NA | NA |
DIS | 1.487 (0.968-2.329) | 0.075 | NA | NA |
mT | 1.717 (0.919-3.312) | 0.096 | NA | NA |
mN | 2.507 (1.467-4.495) | 0.001a | NA | NA |
cM | 5.662 (1.158-40.921) | 0.044a | NA | NA |
cTNM | 3.705 (2.139-7.056) | 0.000a | 42.002 (2.913-605.511) | 0.006a |
mCRM | 3.439 (1.562-7.838) | 0.003a | NA | NA |
mEMVI | 2.613 (1.199-5.852) | 0.017a | NA | NA |
Histological grade | 0.229 (0.092-0.496) | 0.001a | 0.113 (0.020-0.658) | 0.015a |
Table 5 Performance of various radiomics predictive models in the training group as evaluated using the Delong test, integrated discrimination improvement index and net reclassification improvement index
Radiomics prediction models | AUC (95%CI) | Delong test P value | IDI (95%CI) | IDI index P value | NRI (95%CI) | NRI index P value |
T2WI + T1CE | 0.839 (0.757-0.921) | |||||
T2WI | 0.817 (0.733-0.901) | 0.252 | 0.081 (0.031-0.131) | 0.001 | 0.510 (0.104-0.865) | 0.008 |
T1CE | 0.798 (0.707-0.890) | 0.196 | 0.127 (0.064-0.190) | 0.000 | 0.536 (0.255-1.018) | 0.005 |
Table 6 Performance of the clinical model, T2-weighted imaging + contrast-enhanced T1WI fusion sequence radiomics model, and clinical-radiomics model in the training group, as evaluated using the Delong test, integrated discrimination improvement index, and Net reclassification improvement index
Models | AUC (95%CI) | Delong test P value | IDI (95%CI) | IDI index P value | NRI (95%CI) | NRI index P value |
CR model | 0.889 (0.824-0.954) | |||||
Clinical | 0.804 (0.727-0.881) | 0.009 | 0.210 (0.130-0.290) | 0.000 | 0.588 (0.271-0.904) | 0.000 |
T2WI + T1CE | 0.839 (0.757-0.921) | 0.019 | 0.075 (0.026-0.124) | 0.002 | 0.447 (0.164-0.731) | 0.002 |
- Citation: Liu Y, Sun BJT, Zhang C, Li B, Yu XX, Du Y. Preoperative prediction of perineural invasion of rectal cancer based on a magnetic resonance imaging radiomics model: A dual-center study. World J Gastroenterol 2024; 30(16): 2233-2248
- URL: https://www.wjgnet.com/1007-9327/full/v30/i16/2233.htm
- DOI: https://dx.doi.org/10.3748/wjg.v30.i16.2233