MRI-based prediction of the need for wide resection margins in patients with single hepatocellular carcinoma
Surgical resection constitutes a major curative-intent treatment option for resectable hepatocellular carcinoma (HCC) . One of the main challenges in the surgical planning of HCC is to determine the appropriate resection margin to ensure complete tumor removal and low risk of recurrence while preserving as much liver function as possible . Since peritumoral liver parenchyma could contain satellite nodules and microvascular invasion (MVI) that might be radiologically undetectable , a resection margin width ≥ 1 cm is recommended to reduce postoperative early recurrence [ – ]. However, conflicting results have been reported regarding the optimal margin width , and several studies showed limited survival benefits of wide resection margins (≥ 1 cm) compared with narrow resection margins (< 1 cm) . A plausible explanation for the inconsistencies in optimal margin width is that HCC is a biologically heterogeneous malignancy with variegated prognostic benefits from wide resection margins. Furthermore, there are several intrinsic limitations of wide resection margins. For instance, it may carry an increased risk for severe perioperative complications, such as life-threatening bleeding and liver failure , and the feasibility of wide resection margins could be limited by tumor size, location, proximity to large vessels, and functional liver reserve . Given that wide resection margins may be potentially ineffective and risky for some patients, narrow resection margins are conducted for a large proportion of patients in clinical practice . Thus, to guarantee acceptable oncological outcomes, it is crucial to identify patients for whom wide resection margins are more effective than narrow resection margins. Previous research has reported that small tumor size (< 5 cm) , elevated alpha-fetoprotein (AFP, > 100 ng/mL) , [ 18 F]FDG positive lesions , positive circulating tumor cell status , and poorly demarcated gross types  as single indicators favoring the selection of wide resection margin. However, as a biologically heterogeneous malignancy, the prognosis of HCC has been found to vary substantially within any category defined based on a single indicator (e.g., the post-resection survival of HCC < 5 cm varied depending on AFP levels ). Therefore, relying on a single indicator to estimate the survival benefit of wide resection margins in heterogeneous patient cohorts is likely inaccurate. Fortunately, imaging techniques, particularly magnetic resonance imaging (MRI), can display the whole landscape of HCC, potentially providing insights into its heterogeneity in a non-invasive manner. By considering multiple MRI features simultaneously, several MRI-based models have shown promising results for stratifying the risk of recurrence or survival and the potential to identify optimal candidates for HCC treatments . However, there are few studies using the MRI-based model to identify patients who would not achieve adequate oncological radicality with narrow resection margins and may be at lower risk of early recurrence with wide resection margins. Therefore, the aim of this study was to develop an MRI-based score to support the selection between wide- and narrow resection margins, based on the prediction of postoperative early recurrence-free survival (RFS ≤ 24 months) in patients receiving narrow resection margins for a single Barcelona clinic liver cancer (BCLC) 0 or A HCC. 

This single-center retrospective study was approved by the Ethics Committees of West China Hospital, Sichuan University, and the requirement to obtain written informed consent was waived. Patient selection Figure portrays the subjects’ inclusion and exclusion flowchart, in accordance with the standards for reporting of diagnostic accuracy initiative . From December 2011 to May 2022, consecutive patients who fulfilled the following inclusion criteria were identified: (a) age ≥ 18 years; (b) pathologically diagnosed single BCLC 0 or A HCC; (c) underwent curative-intent liver resection; (d) preserved hepatic function (i.e., Child-Pugh class A5 through B7); (e) complete documentation of resection margin width, and (f) underwent preoperative contrast-enhanced MRI within two months prior to surgery. The exclusion criteria were: (a) any previous or concurrent malignancy other than HCC; (b) previous treatment for HCC; (c) ruptured HCC; (d) MR images of inadequate quality for analyses; (e) received non-curative resection ; (f) died from acute post-operative complications within two weeks after surgery; or (g) lack of any follow-up information. This work included 339 previously reported patients , but with distinct study purposes, design, and endpoints. Demographic, laboratory, surgical, and histologic data Demographic, laboratory, surgical, and histopathological data were collected from electronic patient records. A wide- or a narrow-resection margin was defined as the pathological shortest distance from the edge of the tumor to the plane of liver resection being ≥ 1 cm or < 1 cm, as previously described . Further details can be found in the Supplementary Material . Image acquisition and analysis Contrast-enhanced MRI examinations using either extracellular or hepatobiliary contrast agents (HBA) were performed with various 1.5-T or 3.0-T scanners. Image acquisition protocols are detailed in Supplementary Material and Supplementary Table . All MRI images were evaluated by three independent fellowship-trained abdominal radiologists (with 7 years, 10 years, and 3 years of experience in liver MRI, respectively) who were aware of the HCC diagnosis but blinded to all remaining clinical, histopathological, and follow-up information. A total of 51 MRI features were evaluated, including (a) tumor location, (b) imaging features related to tumor aggressiveness (including all liver imaging reporting and data system v2018 features  and other previously reported prognostic features of the tumor ), and (c) features related to the underlying liver condition. Detailed MRI features and their definitions are shown in Supplementary Table . Further information on resolving inter-rater disagreements is described in Supplementary Material . Follow-up and outcome measures After surgery, patients were followed up at one month, every three months for the first two years, and every six months thereafter until death or May 1, 2022. Serum AFP, liver biochemistry, and abdominal ultrasound or contrast-enhanced CT/MRI were included for follow-up examinations. Bone scans, chest CT, head CT/MRI, and biopsies were performed when clinically indicated. The early RFS rate (i.e., the proportion of patients alive and recurrent-free at 24 months) was the primary endpoint for survival analyses as it has been predominantly associated with tumor aggressiveness and resection radicality . Statistical analysis The statistical analyses are detailed in Supplemental Material . Briefly, based on the assumption that achieving insufficient oncologic outcomes with narrow resection margins would benefit more from wide resection margins, an MRI-based model (i.e., MARGIN) for predicting postoperative early RFS in patients with narrow resection margins was developed, which served as the basis for predicting the need for wide resection margins. Score development and validation To ensure effective multivariable regression analyses, the sample size was estimated for at least five outcome events per variable . Eligible patients with narrow resection margins were randomly divided into training and testing datasets at a ratio of 7:3. In the training dataset, predictive preoperative demographic, laboratory, and MRI variables were identified using univariable and multivariable Cox regression analyses with backward step-wise selection and five-fold cross-validation (cutoffs detailed in Supplemental Table ). Inter-variable collinearity was calculated using Spearman’s correlation analysis. A scoring system was formulated based on the statistically significant variables from the multivariable Cox analysis weighted by their respective β coefficients, with the largest β coefficient scaled as 12 points and the remaining proportionally rounded to the nearest integer to improve clinical utility. Model discrimination was evaluated using the concordance index ( C -index) and time-dependent area under the curve (AUC). To divide the patients into high- and low-risk groups for early recurrence, the optimal threshold value of the score was determined at the 75th percentile based on the training dataset. Score utility in informing the need for wide resection margins Based on pretreatment factors that may have influenced survival and resection margin selection (i.e., cirrhosis , ALBI score , tumor size , and tumor location ), a 1:1 optimal propensity score matching was performed between patients who received narrow and wide resection margins. Survival outcomes were estimated with the Kaplan–Meier method and compared using the log-rank test. In MARGIN-predicted high-risk patients, the prognostic value of margin width was evaluated by multivariable analyses in conjunction with other previously published prognostic variables. Furthermore, details of incremental prognostic values of the MARGIN score to the preoperative Early Recurrence After Surgery for Liver Tumor (ERASL-pre) score  are described in the Supplementary Material. R (version 4.2.2; R Foundation for Statistical Computing) was used for statistical analysis. A two-sided p < 0.05 was considered statistically significant. 

Figure portrays the subjects’ inclusion and exclusion flowchart, in accordance with the standards for reporting of diagnostic accuracy initiative . From December 2011 to May 2022, consecutive patients who fulfilled the following inclusion criteria were identified: (a) age ≥ 18 years; (b) pathologically diagnosed single BCLC 0 or A HCC; (c) underwent curative-intent liver resection; (d) preserved hepatic function (i.e., Child-Pugh class A5 through B7); (e) complete documentation of resection margin width, and (f) underwent preoperative contrast-enhanced MRI within two months prior to surgery. The exclusion criteria were: (a) any previous or concurrent malignancy other than HCC; (b) previous treatment for HCC; (c) ruptured HCC; (d) MR images of inadequate quality for analyses; (e) received non-curative resection ; (f) died from acute post-operative complications within two weeks after surgery; or (g) lack of any follow-up information. This work included 339 previously reported patients , but with distinct study purposes, design, and endpoints. 

Demographic, laboratory, surgical, and histopathological data were collected from electronic patient records. A wide- or a narrow-resection margin was defined as the pathological shortest distance from the edge of the tumor to the plane of liver resection being ≥ 1 cm or < 1 cm, as previously described . Further details can be found in the Supplementary Material . 

Contrast-enhanced MRI examinations using either extracellular or hepatobiliary contrast agents (HBA) were performed with various 1.5-T or 3.0-T scanners. Image acquisition protocols are detailed in Supplementary Material and Supplementary Table . All MRI images were evaluated by three independent fellowship-trained abdominal radiologists (with 7 years, 10 years, and 3 years of experience in liver MRI, respectively) who were aware of the HCC diagnosis but blinded to all remaining clinical, histopathological, and follow-up information. A total of 51 MRI features were evaluated, including (a) tumor location, (b) imaging features related to tumor aggressiveness (including all liver imaging reporting and data system v2018 features  and other previously reported prognostic features of the tumor ), and (c) features related to the underlying liver condition. Detailed MRI features and their definitions are shown in Supplementary Table . Further information on resolving inter-rater disagreements is described in Supplementary Material . 

After surgery, patients were followed up at one month, every three months for the first two years, and every six months thereafter until death or May 1, 2022. Serum AFP, liver biochemistry, and abdominal ultrasound or contrast-enhanced CT/MRI were included for follow-up examinations. Bone scans, chest CT, head CT/MRI, and biopsies were performed when clinically indicated. The early RFS rate (i.e., the proportion of patients alive and recurrent-free at 24 months) was the primary endpoint for survival analyses as it has been predominantly associated with tumor aggressiveness and resection radicality . 

The statistical analyses are detailed in Supplemental Material . Briefly, based on the assumption that achieving insufficient oncologic outcomes with narrow resection margins would benefit more from wide resection margins, an MRI-based model (i.e., MARGIN) for predicting postoperative early RFS in patients with narrow resection margins was developed, which served as the basis for predicting the need for wide resection margins. Score development and validation To ensure effective multivariable regression analyses, the sample size was estimated for at least five outcome events per variable . Eligible patients with narrow resection margins were randomly divided into training and testing datasets at a ratio of 7:3. In the training dataset, predictive preoperative demographic, laboratory, and MRI variables were identified using univariable and multivariable Cox regression analyses with backward step-wise selection and five-fold cross-validation (cutoffs detailed in Supplemental Table ). Inter-variable collinearity was calculated using Spearman’s correlation analysis. A scoring system was formulated based on the statistically significant variables from the multivariable Cox analysis weighted by their respective β coefficients, with the largest β coefficient scaled as 12 points and the remaining proportionally rounded to the nearest integer to improve clinical utility. Model discrimination was evaluated using the concordance index ( C -index) and time-dependent area under the curve (AUC). To divide the patients into high- and low-risk groups for early recurrence, the optimal threshold value of the score was determined at the 75th percentile based on the training dataset. Score utility in informing the need for wide resection margins Based on pretreatment factors that may have influenced survival and resection margin selection (i.e., cirrhosis , ALBI score , tumor size , and tumor location ), a 1:1 optimal propensity score matching was performed between patients who received narrow and wide resection margins. Survival outcomes were estimated with the Kaplan–Meier method and compared using the log-rank test. In MARGIN-predicted high-risk patients, the prognostic value of margin width was evaluated by multivariable analyses in conjunction with other previously published prognostic variables. Furthermore, details of incremental prognostic values of the MARGIN score to the preoperative Early Recurrence After Surgery for Liver Tumor (ERASL-pre) score  are described in the Supplementary Material. R (version 4.2.2; R Foundation for Statistical Computing) was used for statistical analysis. A two-sided p < 0.05 was considered statistically significant. 

To ensure effective multivariable regression analyses, the sample size was estimated for at least five outcome events per variable . Eligible patients with narrow resection margins were randomly divided into training and testing datasets at a ratio of 7:3. In the training dataset, predictive preoperative demographic, laboratory, and MRI variables were identified using univariable and multivariable Cox regression analyses with backward step-wise selection and five-fold cross-validation (cutoffs detailed in Supplemental Table ). Inter-variable collinearity was calculated using Spearman’s correlation analysis. A scoring system was formulated based on the statistically significant variables from the multivariable Cox analysis weighted by their respective β coefficients, with the largest β coefficient scaled as 12 points and the remaining proportionally rounded to the nearest integer to improve clinical utility. Model discrimination was evaluated using the concordance index ( C -index) and time-dependent area under the curve (AUC). To divide the patients into high- and low-risk groups for early recurrence, the optimal threshold value of the score was determined at the 75th percentile based on the training dataset. 

Based on pretreatment factors that may have influenced survival and resection margin selection (i.e., cirrhosis , ALBI score , tumor size , and tumor location ), a 1:1 optimal propensity score matching was performed between patients who received narrow and wide resection margins. Survival outcomes were estimated with the Kaplan–Meier method and compared using the log-rank test. In MARGIN-predicted high-risk patients, the prognostic value of margin width was evaluated by multivariable analyses in conjunction with other previously published prognostic variables. Furthermore, details of incremental prognostic values of the MARGIN score to the preoperative Early Recurrence After Surgery for Liver Tumor (ERASL-pre) score  are described in the Supplementary Material. R (version 4.2.2; R Foundation for Statistical Computing) was used for statistical analysis. A two-sided p < 0.05 was considered statistically significant. 

Patients This study included 419 patients (median age, 54 years; 361 men), 282 (67.3%) with narrow resection margins (Table ). Patients with wide resection margins had smaller tumors (median size, 2.73 cm vs 3.27 cm, respectively; p = 0.001) which were more frequently located in the left lateral section (27.7% vs 9.2%, respectively, p < 0.001) compared with those with narrow resection margins. No difference in pathological tumor differentiation, MVI, satellite nodules, or liver capsular involvement was observed between the two groups ( p values, 0.11–0.58). During a median follow-up time of 32.1 months, overall recurrence and early recurrence occurred in 35.3% (148/419) and 27.7% (116/419) of patients, respectively. Among the latter, 66.4% (77/116) exclusively developed intrahepatic recurrence, 3.4% (4/116) exclusively developed macrovascular invasion, 12.9% (15/116) exclusively developed extrahepatic metastases, and 17.2% (20/116) had recurrent tumors involving multiple sites. Patients with wide resection margins had higher rates of early RFS (78.3% vs 64.4%, respectively; p = 0.003) and overall RFS (60.6% vs 34.4%, respectively; p = 0.002) than their counterparts (Supplementary Fig. ). Development of the MARGIN score Based on patients with narrow resection margins, 13 preoperative variables (four clinical and nine MRI variables) were associated with early RFS rate at univariable Cox regression analyses ( p values, 0.001–0.041, Table and Supplemental Table ). After accounting for collinearity, seven independent factors were further analyzed (Table ). In the multivariable analysis, five variables were associated with early RFS, including age (HR = 0.97; 95% confidence interval [CI]: 0.95–0.99; p = 0.005), preoperative AFP > 400 ng/mL (HR = 1.77; 95% CI: 1.03–3.03; p = 0.04), protein induced by vitamin K absence or antagonist-II (PIVKA-II) > 200 mAU/mL (HR = 2.38; 95% CI: 1.39–4.05; p = 0.002), radiological involvement of liver capsule (HR = 2.36; 95% CI: 1.32–4.24; p = 0.004), and presence of an infiltrative appearance (HR = 3.64; 95% CI: 1.43–9.29; p = 0.01). These predictors were incorporated into the MARGIN score as follows (Fig. ). The MARGIN score = 5.3 × serum AFP in ng/mL (> 400, 1; ≤ 400, 0) + 8.0 × serum PIVKA-II in mAU/mL (> 200, 1; ≤ 200, 0) – 0.3 × age + 8.0 × radiological involvement of liver capsule (absent, 0; present, 1) + 12.0 × infiltrative appearance (absent, 0; present, 1). The inter-rater agreement was excellent for the MARGIN score (intraclass correlation coefficient, 0.882; 95% CI: 0.863–0.899) and for the MARGIN risk strata (Fleiss κ value, 0.827; 95% CI: 0.748–0.906). Supplemental Table summarizes the frequencies and inter-rater agreement of evaluated MR features. Validation of the MARGIN score The MARGIN score demonstrated a C -index of 0.74 (95% CI: 0.68–0.80) in the training dataset and 0.75 (95% CI: 0.65–0.84) in the testing dataset. The td-AUCs of the MARGIN score in predicting 1- and 2-year RFS were 0.81 (95% CI: 0.73–0.88) and 0.72 (95% CI: 0.63–0.80) for the training dataset, and 0.78 (95% CI: 0.63–0.93) and 0.71 (95% CI: 0.57–0.85) for the testing dataset, respectively. Supplementary Fig. illustrates the 2-year calibration and decision curves. Recurrence risk stratification In the training dataset, the MARGIN score ranged from − 22.2 to 24.3. Patients were classified as low- ( MARGIN score < − 1.3) or high-risk ( MARGIN score ≥ − 1.3). Figure illustrates preoperative MRI images of representative patients from various risk profiles. For patients with narrow resection margins, the high-risk group stratified by MARGIN (≥ − 1.3 points) had a lower cumulative rate of early RFS (both datasets p < 0.001) and overall RFS (both datasets p < 0.001, Fig. ) at different time points than the low-risk group. To shed light on the biological underpinnings of MARGIN, known prognostic histopathologic features were compared between risk groups and presented in Supplemental Material and Supplement Table . Application of MARGIN in informing the benefit of wide resection margins After propensity score matching, 137 pairs of patients were matched for the narrow and wide resection margin groups, with standardized mean difference values ranging from 0.015 to 0.099. The characteristics of the propensity-score-matched cohorts are summarized in Supplement Table . For the entire matched cohort, no difference in early RFS rate was observed between patients with wide or narrow resection margins (78.3% vs 70.1%; HR = 0.62; 95% CI: 0.37–1.01; p = 0.06, Fig. ). However, after risk stratification based on MARGIN score, wide resection margins were associated with higher early RFS rate in the high-risk group (71.1% vs 41.0%; HR = 0.35; 95% CI: 0.14–0.87; p = 0.02, Fig. ), but not in the low-risk group (79.7% vs 76.1%; HR = 0.75; 95% CI: 0.41–1.37; p = 0.36, Fig. ). Similar results were observed in the subgroup analysis of patients with tumors of 2–5 cm. Specifically, a wide resection margin was associated with an improved early RFS rate in the high-risk group (80.5% vs 25.0%; HR = 0.16; 95% CI: 0.03–0.78; p = 0.02), but not in the low-risk group (78.4% vs 76.0%; HR = 0.76; 95% CI: 0.34–1.69; p = 0.50). For high-risk patients, margin width was the only prognostic factor for early RFS rate in the Cox regression analysis (HR = 0.34; 95% CI: 0.13–0.91; p = 0.03; Table ). Likewise, based on the entire matched cohort, no difference in overall RFS rate was observed between patients with wide or narrow resection margins (60.6% vs 54.1%, respectively; HR = 0.67; 95% CI: 0.43–1.03; p = 0.07, Fig. ). After risk stratification based on MARGIN score, wide resection margins were associated with improved overall RFS rate in the high-risk group (64.0% vs 12.8%; HR = 0.30; 95% CI: 0.13–0.69; p = 0.01, Fig. ), but not in the low-risk group (58.8% vs 62.8%; HR = 0.86; 95% CI: 0.51–1.45; p = 0.57, Fig. ). For high-risk patients, margin width was also the only prognostic factor for overall RFS rate at the Cox regression analysis (HR = 0.29; 95% CI: 0.12–0.72; p = 0.007; Supplement Table ). The incremental value of the MARGIN score to ERASL-pre is shown in Supplemental Fig. and Supplemental Material . 

This study included 419 patients (median age, 54 years; 361 men), 282 (67.3%) with narrow resection margins (Table ). Patients with wide resection margins had smaller tumors (median size, 2.73 cm vs 3.27 cm, respectively; p = 0.001) which were more frequently located in the left lateral section (27.7% vs 9.2%, respectively, p < 0.001) compared with those with narrow resection margins. No difference in pathological tumor differentiation, MVI, satellite nodules, or liver capsular involvement was observed between the two groups ( p values, 0.11–0.58). During a median follow-up time of 32.1 months, overall recurrence and early recurrence occurred in 35.3% (148/419) and 27.7% (116/419) of patients, respectively. Among the latter, 66.4% (77/116) exclusively developed intrahepatic recurrence, 3.4% (4/116) exclusively developed macrovascular invasion, 12.9% (15/116) exclusively developed extrahepatic metastases, and 17.2% (20/116) had recurrent tumors involving multiple sites. Patients with wide resection margins had higher rates of early RFS (78.3% vs 64.4%, respectively; p = 0.003) and overall RFS (60.6% vs 34.4%, respectively; p = 0.002) than their counterparts (Supplementary Fig. ). 

Based on patients with narrow resection margins, 13 preoperative variables (four clinical and nine MRI variables) were associated with early RFS rate at univariable Cox regression analyses ( p values, 0.001–0.041, Table and Supplemental Table ). After accounting for collinearity, seven independent factors were further analyzed (Table ). In the multivariable analysis, five variables were associated with early RFS, including age (HR = 0.97; 95% confidence interval [CI]: 0.95–0.99; p = 0.005), preoperative AFP > 400 ng/mL (HR = 1.77; 95% CI: 1.03–3.03; p = 0.04), protein induced by vitamin K absence or antagonist-II (PIVKA-II) > 200 mAU/mL (HR = 2.38; 95% CI: 1.39–4.05; p = 0.002), radiological involvement of liver capsule (HR = 2.36; 95% CI: 1.32–4.24; p = 0.004), and presence of an infiltrative appearance (HR = 3.64; 95% CI: 1.43–9.29; p = 0.01). These predictors were incorporated into the MARGIN score as follows (Fig. ). The MARGIN score = 5.3 × serum AFP in ng/mL (> 400, 1; ≤ 400, 0) + 8.0 × serum PIVKA-II in mAU/mL (> 200, 1; ≤ 200, 0) – 0.3 × age + 8.0 × radiological involvement of liver capsule (absent, 0; present, 1) + 12.0 × infiltrative appearance (absent, 0; present, 1). The inter-rater agreement was excellent for the MARGIN score (intraclass correlation coefficient, 0.882; 95% CI: 0.863–0.899) and for the MARGIN risk strata (Fleiss κ value, 0.827; 95% CI: 0.748–0.906). Supplemental Table summarizes the frequencies and inter-rater agreement of evaluated MR features. 

The MARGIN score demonstrated a C -index of 0.74 (95% CI: 0.68–0.80) in the training dataset and 0.75 (95% CI: 0.65–0.84) in the testing dataset. The td-AUCs of the MARGIN score in predicting 1- and 2-year RFS were 0.81 (95% CI: 0.73–0.88) and 0.72 (95% CI: 0.63–0.80) for the training dataset, and 0.78 (95% CI: 0.63–0.93) and 0.71 (95% CI: 0.57–0.85) for the testing dataset, respectively. Supplementary Fig. illustrates the 2-year calibration and decision curves. 

In the training dataset, the MARGIN score ranged from − 22.2 to 24.3. Patients were classified as low- ( MARGIN score < − 1.3) or high-risk ( MARGIN score ≥ − 1.3). Figure illustrates preoperative MRI images of representative patients from various risk profiles. For patients with narrow resection margins, the high-risk group stratified by MARGIN (≥ − 1.3 points) had a lower cumulative rate of early RFS (both datasets p < 0.001) and overall RFS (both datasets p < 0.001, Fig. ) at different time points than the low-risk group. To shed light on the biological underpinnings of MARGIN, known prognostic histopathologic features were compared between risk groups and presented in Supplemental Material and Supplement Table . 

After propensity score matching, 137 pairs of patients were matched for the narrow and wide resection margin groups, with standardized mean difference values ranging from 0.015 to 0.099. The characteristics of the propensity-score-matched cohorts are summarized in Supplement Table . For the entire matched cohort, no difference in early RFS rate was observed between patients with wide or narrow resection margins (78.3% vs 70.1%; HR = 0.62; 95% CI: 0.37–1.01; p = 0.06, Fig. ). However, after risk stratification based on MARGIN score, wide resection margins were associated with higher early RFS rate in the high-risk group (71.1% vs 41.0%; HR = 0.35; 95% CI: 0.14–0.87; p = 0.02, Fig. ), but not in the low-risk group (79.7% vs 76.1%; HR = 0.75; 95% CI: 0.41–1.37; p = 0.36, Fig. ). Similar results were observed in the subgroup analysis of patients with tumors of 2–5 cm. Specifically, a wide resection margin was associated with an improved early RFS rate in the high-risk group (80.5% vs 25.0%; HR = 0.16; 95% CI: 0.03–0.78; p = 0.02), but not in the low-risk group (78.4% vs 76.0%; HR = 0.76; 95% CI: 0.34–1.69; p = 0.50). For high-risk patients, margin width was the only prognostic factor for early RFS rate in the Cox regression analysis (HR = 0.34; 95% CI: 0.13–0.91; p = 0.03; Table ). Likewise, based on the entire matched cohort, no difference in overall RFS rate was observed between patients with wide or narrow resection margins (60.6% vs 54.1%, respectively; HR = 0.67; 95% CI: 0.43–1.03; p = 0.07, Fig. ). After risk stratification based on MARGIN score, wide resection margins were associated with improved overall RFS rate in the high-risk group (64.0% vs 12.8%; HR = 0.30; 95% CI: 0.13–0.69; p = 0.01, Fig. ), but not in the low-risk group (58.8% vs 62.8%; HR = 0.86; 95% CI: 0.51–1.45; p = 0.57, Fig. ). For high-risk patients, margin width was also the only prognostic factor for overall RFS rate at the Cox regression analysis (HR = 0.29; 95% CI: 0.12–0.72; p = 0.007; Supplement Table ). The incremental value of the MARGIN score to ERASL-pre is shown in Supplemental Fig. and Supplemental Material . 

Based on 282 patients with curative-intent narrow resection margins, we developed a prognostic score named “ MARGIN ” to predict the early RFS rate. Utilizing five preoperative features, the MARGIN score achieved a C -index of 0.75 in the testing dataset, effectively stratifying patients into prognostically distinct high- ( MARGIN score ≥ − 1.3) and low-risk ( MARGIN score < − 1.3) groups. When applied to 137 pairs of propensity-score-matched patients, wide resection margins were associated with an improved early RFS rate for the MARGIN -predicted high-risk patients ( p = 0.02), but not for the low-risk ones ( p = 0.36). The radicality of HCC resection is influenced by surgical choice and directly affects survival outcomes . Wide resection margins have been widely correlated with a lower risk of early recurrence compared with narrow resection margins [ , , ], which aligns with our findings in all enrolled patients (early RFS rate, 78.3% vs 64.4%; p = 0.003). However, several factors (i.e., tumor size, tumor location and liver function [ , , ]) may influence margin width selection, as well as survival outcomes, leaving it unclear whether a wide resection margin is a surrogate of underlying tumor biology or truly a technical issue that independently affects survival. Notably, after propensity-score matching, no difference in early RFS rate was detected between the wide and narrow resection margin groups (78.3% vs 70.1% p = 0.06), indicating that the prognostic significance of margin width varied across patient subpopulations. Given the uncertainties and potential impairments caused by improper resections, adopting a benefit-based tailored treatment strategy will prove to be more effective than a blanket “treat all” approach. The MARGIN score allows for better estimates of an individual patient’s likelihood of benefiting from wide resection margins. Among propensity-score matched patients, an improved early RFS rate was observed for wide resection margins in the MARGIN high-risk patients (71.1% vs 41.0%; p = 0.02), but not for the low-risk ones (79.7% vs 76.1%; p = 0.36). Additionally, for patients with MARGIN -predicted high-risk status, margin width was a significant predictor of early recurrence, even after adjusting for established prognostic factors. MARGIN also enabled the identification of patients who were more likely to benefit from wide resection margins within the ERASL-predicted low-risk category, highlighting the incremental prognostic value of the MARGIN to the ERASL which is a widely validated post-resection predicting score. Furthermore, our multivariable risk prediction is more effective than conventional “one-variable” subgroup analyses, as it accounts for potential interactions and confounding effects of other variables. The MARGIN score was constructed based on comprehensive clinic-radiological features (including 11 clinical and 51 radiologic features for each patient) with rigorous modeling methodologies, making it more relevant to individual patients than recommendations based on coarse groupings of large numbers of heterogeneous patients . Notably, the MARGIN score was exclusively developed for patients with BCLC 0 or A HCC and well-preserved liver function, whose prognosis is well-known in relation to surgical choice . Despite being the optimal surgical candidate as recommended by major guidelines, whether MARGIN could be extrapolated to inform the selection of wide or narrow resection margin in patients with tumors beyond a single BCLC 0/A stage (e.g., multinodular BCLC A tumor) remains to be elucidated. The MARGIN score emphasized the potential of imaging features (i.e., infiltrative appearance and radiologic involvement of the liver capsule) in assisting individualized treatment. Specifically, infiltrative appearance is a well-established adverse prognostic feature of HCC and has been incorporated into the most recent BCLC staging system . The infiltrative appearance has been associated with poorer differentiation, more frequent MVI, reduced capsule formation, and higher expression of stemness-related markers on pathology . For infiltrative HCC, wide resection margins have been related to a survival benefit compared to narrow resection margins . Radiologic involvement of the liver capsule was also predictive of early recurrence, along with narrow resection margins, potentially due to larger tumor size and increased capsular spread . Overall, the MARGIN score can effectively profile tumor biologic aggressiveness. In particular, MARGIN -predicted high-risk status was associated with more frequent MVI, poorer differentiation, and liver capsule involvement in pathology. The MARGIN score was derived from semantic imaging features that are user-friendly. Beyond semantics, several studies have used quantitative radiomics to predict post-resection outcomes in HCC . However, the complexity of radiomic analysis requires specialized software and expertise, making it less accessible for clinical adoption. Notably, despite an excellent inter-rater agreement for MARGIN and MARGIN -defined risk groups, a suboptimal agreement was found for MARGIN -included imaging features. The inadequate agreement for imaging features may have been inherent to subjective manual assessment, which was consistent with previous studies . These results highlight the need to enhance the reproducibility of imaging assessment, possibly through standardized lexicons and objective criteria. This study had several limitations. First, it was a single-center study with a relatively small sample size. Therefore, no external validation was available to test and refine the MARGIN score. Second, up to 79.4% of the included patients had chronic hepatitis B. Therefore, our model may not be applicable to patients with non-hepatitis B etiology. Third, our database did not include information on whether liver resections were anatomical. Although Liu et al  demonstrated wide resection margins are more important than anatomical resection for prognosis in patients with MVI-positive HCC, we were unable to determine which factor, anatomical resection or wide resection margins, had a greater influence on survival results. Therefore, further prospective multi-center studies are warranted to validate our findings, ideally in the setting of clinical trials. In conclusion, in patients who underwent curative-intent resection for single BCLC 0 or A HCC, we developed and validated a prognostic score called the MARGIN for early recurrence based on five preoperative clinical and MRI features. Wide resection margins were associated with improved early RFS rate for the MARGIN -predicted high-risk patients, but not for the low-risk ones. 

ELECTRONIC SUPPLEMENTARY MATERIAL 

