Predictive value of preoperative subcutaneous and intramuscular adipose tissue for the occurrence of postoperative liver metastasis in gastric cancer patients undergoing radical gastrectomy
Highlight box
Key findings
• In this study, we found preoperative subcutaneous adipose tissue area (SATA) and intramuscular adipose tissue area (IATA) at the L3 level in computed tomography (CT) image were significant predictors of postoperative liver metastasis in gastric cancer patients undergoing radical gastrectomy.
What is known and what is new?
• Body compositions were associated with the clinical outcomes in patients with malignant tumors.
• We additionally found postoperative liver metastasis for gastric cancer patients undergoing radical gastrectomy showed larger IATA while smaller SATA before the surgery.
What is the implication, and what should change now?
• Preoperative body composition, especially IATA and SATA, should be assessed in patients with gastric cancer. This may help to predict the occurrence of liver metastasis after radical gastrectomy.
Introduction
The incidence and mortality rates of gastric cancer (GC) both ranked fifth in the world, and the mortality rate particularly ranked third in China (1). Radical gastrectomy is the only curative treatment for GC thus far. The liver is the primary target organ for hematogenous metastasis after GC surgery, with a liver metastasis rate of up to 30% after radical gastrectomy (2). The median interval time for liver metastasis after radical gastrectomy was 14 months, the median survival time was 11 months, and the 5-year survival rate was less than 20% (3). Hepatic resection could increase the 5-year overall survival (OS) (4).
Previous studies showed that body composition, including visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and skeletal muscle (SM) were associated with the clinical outcomes of patients with malignant tumors (5,6). GC patients were more likely to have body composition changes due to reduced nutritional intake, tumor progression, and systemic inflammation (7,8). In recent years, more and more studies have used computed tomography (CT) images to assess muscle mass and fat distribution (9). However, no studies have reported the correlation between body composition and the occurrence of liver metastasis in GC following radical gastrectomy.
Therefore, this study investigated the relationship between preoperative CT-based body composition and the occurrence of liver metastasis after radical gastrectomy in GC patients. We present this article in accordance with the TRIPOD reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-82/rc).
Methods
Study population
The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study protocol was approved by the Institutional Ethics Review Committee of The Affiliated Cancer Hospital of Nanjing Medical University (Jiangsu Cancer Hospital) (No. 2023ke-kuai055-GZ-01) before the study was initiated. Due to the retrospective nature of the study, and individual consent was not required. Patients who underwent radical gastrectomy for GC at a single center from January 2012 to December 2023 were retrospectively studied. The inclusion criteria were age ≥18 years, diagnosed as adenocarcinoma according to the pathology. The exclusion criteria were the simultaneous presence of other malignant tumors, treatment history of the tumor, presence of distant metastases before the surgery, metastases to other sites but liver, no liver metastasis after the surgery but less than 3-year follow-up, and the absence of available CT images (Figure 1).
Data collection and grouping
Demographic data included age, gender, height, preoperative body weight and body mass index (BMI), history of smoking, alcohol drinking, diabetes, and hypertension. Preoperative laboratory tests including carbohydrate antigen 199 (CA199), carcinoembryonic antigen (CEA), and alpha-fetoprotein (AFP) were also recorded. Operative information contained tumor location and operation methods. Pathological information included Tumor-Node-Metastasis (TNM) staging (according to American Joint Committee on Cancer 8th edition), tumor differentiation grade, lymphovascular invasion (LVI), perineural invasion (PNI), Lauren classification, Ki67, and HER-2. Included patients were divided into the control and liver metastasis groups according to whether there was visible liver metastasis (which could be accompanied by metastases at other sites) within 3 years after the surgery.
Body composition assessment with CT images
Preoperative CT images were analyzed using the SliceOmatic software Version 5 (TomoVision, Montreal, Canada). The portal venous phase of the enhanced sequence at the transverse L3 level was selected to estimate body composition (10). The ranges of attenuation value for muscle and adipose tissue were set as follows: SM with −29 to +150 Hounsfield Units (HU), VAT with −150 to −50 HU, SAT with −190 to −30 HU and intramuscular adipose tissue (IAT) with −190 to −30 HU (11). The muscle and adipose tissue at the L3 level were semiautomatically outlined according to the above HU settings (Figure 2). Group assignments were not known during the analysis of body composition.
After all compositions were outlined, the cross-sectional area (CSA, cm2) of SM, VAT, SAT, and IAT was measured and recorded as SM area (SMA), VAT area (VATA), SAT area (SATA), and IAT area (IATA).
Sample size
Power calculations in a logistic regression model indicated a minimal sample of 280 patients to achieve power of 0.85 and significance of 0.05.
Statistical analysis
Statistical analysis was performed using SPSS Statistics Version 27.0. Continuous data were presented as the mean with standard deviation, and categorical data were presented as the number and proportion. Differences between groups were analyzed using the independent t-test for continuous variables that conformed to normal distribution, or the Mann-Whitney U test for continuous variables that did not conform to normal distribution and categorical variables. Multivariate Logistic regression analysis was used to determine independent risk factors for liver metastasis. The predictive performances of significant factors were measured using the receiver operating characteristic (ROC) analysis, and the area under the ROC curve (AUC) was calculated. Interobserver reliabilities were tested using intraclass correlation coefficients (ICCs) to assess the reliability of measurements of VATA, SATA, IATA and SMA with a sample size of 30 random subjects measured by 2 evaluators. P<0.05 was considered to indicate a statistically significant difference.
Results
Study grouping and common information
A total of 300 patients were included in this study, with 77 in the liver metastasis group and 223 in the control group. Compared with the control group, the liver metastasis group contained more males (86% vs. 64%, P<0.001), presented older age (60.92±10.58 vs. 57.07±10.04 years, P=0.004), higher T and N stage (P<0.001 for both), higher incidence of moderately-poorly and poorly differentiated cell grade (P<0.001), increased LVI and PNI (53% vs. 29%, P<0.001 and 56% vs. 39%, P=0.01, respectively), higher incidence of abnormal CEA (35% vs. 21%, P=0.01), CA199 (17% vs. 7%, P=0.01) and AFP (17% vs. 6%, P=0.003) (Table 1).
Table 1
| Factors | Liver metastasis group (n=77) | Control group (n=223) | P |
|---|---|---|---|
| Age, years, mean ± SD | 60.92±10.58 | 57.07±10.04 | 0.004 |
| Sex, n [%] | <0.001 | ||
| Male | 66 [86] | 143 [64] | |
| Female | 11 [14] | 80 [36] | |
| BMI, kg/m2, mean ± SD | 23.35±2.98 | 23.72±3.21 | 0.38 |
| Hypertension, n [%] | 17 [22] | 46 [21] | 0.79 |
| Diabetes, n [%] | 11 [14] | 18 [8] | 0.11 |
| Smoking, n [%] | 19 [25] | 43 [19] | 0.31 |
| Alcohol drinking, n [%] | 8 [10] | 20 [9] | 0.71 |
| Tumor location, n [%] | 0.46 | ||
| Upper | 23 [30] | 57 [26] | |
| Not upper | 54 [70] | 166 [74] | |
| Scope of surgery, n [%] | 0.19 | ||
| Whole stomach | 33 [43] | 76 [34] | |
| Proximal stomach | 8 [10] | 28 [13] | |
| Distal stomach | 36 [47] | 119 [53] | |
| T stage, n [%] | <0.001 | ||
| T1 | 7 [9] | 55 [25] | |
| T2 | 11 [14] | 56 [25] | |
| T3 | 27 [35] | 49 [22] | |
| T4 | 32 [42] | 63 [28] | |
| N stage, n [%] | <0.001 | ||
| N0 | 15 [19] | 102 [46] | |
| N1 | 15 [19] | 41 [18] | |
| N2 | 21 [27] | 51 [23] | |
| N3 | 26 [34] | 29 [13] | |
| Cell grade, n [%] | <0.001 | ||
| Well differentiated | 2 [3] | 3 [1] | |
| Moderately differentiated | 4 [5] | 34 [15] | |
| Moderately-poorly differentiated | 56 [73] | 92 [41] | |
| Poorly differentiated | 15 [19] | 94 [42] | |
| Lauren classification, n [%]† | 0.67 | ||
| Intestinal type | 24 [33] | 46 [23] | |
| Diffuse type | 16 [22] | 72 [36] | |
| Mixed type | 32 [44] | 81 [41] | |
| Lymphovascular invasion, n [%] | <0.001 | ||
| Yes | 41 [53] | 65 [29] | |
| No | 36 [47] | 158 [71] | |
| Perineural invasion, n [%] | 0.01 | ||
| Yes | 43 [56] | 88 [39] | |
| No | 34 [44] | 135 [61] | |
| Ki67, n [%]‡ | 0.94 | ||
| >50 | 49 [68] | 100 [68] | |
| ≤50 | 23 [32] | 48 [32] | |
| HER-2, n [%]§ | 0.61 | ||
| Negative | 61 [88] | 142 [93] | |
| Positive | 8 [12] | 10 [7] | |
| CEA, n [%] | 0.01 | ||
| Normal | 50 [65] | 176 [79] | |
| Abnormal | 27 [35] | 47 [21] | |
| CA199, n [%] | 0.01 | ||
| Normal | 64 [83] | 207 [93] | |
| Abnormal | 13 [17] | 16 [7] | |
| AFP, n [%] | 0.003 | ||
| Normal | 64 [83] | 210 [94] | |
| Abnormal | 13 [17] | 13 [6] |
†, 5 patients missed in metastasis group and 24 missed in control group; ‡, 5 patients missed in metastasis group and 75 missed in control group; §, 8 patients missed in metastasis group and 71 missed in control group. AFP, alpha-fetoprotein; BMI, body mass index; CA199, carbohydrate antigen 199; CEA, carcinoembryonic antigen; N, node; SD, standard deviation; T, tumor.
Comparisons of body compositions between two groups
Compared with the control group, the liver metastasis group showed significantly larger IATA (7.5±4.78 vs. 5.73±3.78 cm2, P=0.002) while smaller SATA (96.19±50.60 vs. 112.96±51.48 cm2, P=0.009) (Figure 2, Table 2).
Table 2
| Factors | Liver metastasis group (n=77) | Control group (n=223) | P |
|---|---|---|---|
| VATA (cm2) | 93.93±66.06 | 96.13±67.09 | 0.86 |
| SATA (cm2) | 96.19±50.6 | 112.96±51.48 | 0.009 |
| IATA (cm2) | 7.5±4.78 | 5.73±3.78 | 0.002 |
| SMA (cm2) | 137.81±25.79 | 132.25±28.73 | 0.12 |
Data are presented as the mean ± standard deviation. IATA, intramuscular adipose tissue area; SATA, subcutaneous adipose tissue area; SMA, skeletal muscle area; VATA, visceral adipose tissue area.
The interobserver reliability evaluated by ICCs was more than 0.9 for VATA, SATA, IATA, and SMA, indicating a good level of reliability (Table 3).
Table 3
| Factors | ICC | 95% CI | P |
|---|---|---|---|
| VATA (cm2) | 0.949 | 0.897–0.975 | <0.001 |
| SATA (cm2) | 0.978 | 0.955–0.990 | <0.001 |
| IATA (cm2) | 0.919 | 0.674–0.971 | <0.001 |
| SMA (cm2) | 0.948 | 0.866–0.977 | <0.001 |
CI, confidence interval; IATA, intramuscular adipose tissue area; ICC, intraclass correlation coefficient; SATA, subcutaneous adipose tissue area; SMA, skeletal muscle area; VATA, visceral adipose tissue area.
Independent risk factors of liver metastasis
Sex, age, T and N stage, cell grade, LVI, PNI, CEA, CA199, AFP, SATA, and IATA were included for further logistic regression analysis. N stage (P=0.03), cell grade (P=0.01), AFP (P=0.04), and IATA (P=0.04) were independent risk factors for liver metastasis after GC surgery (Table 4).
Table 4
| Factors | B | OR | 95% CI | P |
|---|---|---|---|---|
| Sex | −0.506 | 0.603 | 0.251–1.449 | 0.26 |
| Age, years | 0.008 | 1.008 | 0.972–1.045 | 0.66 |
| T stage | 0.169 | 1.184 | 0.828–1.693 | 0.39 |
| N stage | 0.404 | 1.498 | 1.099–2.043 | 0.03 |
| Cell grade | −0.499 | 0.607 | 0.413–0.894 | 0.01 |
| LVI | −0.478 | 0.620 | 0.299–1.286 | 0.20 |
| PNI | 0.332 | 1.394 | 0.665–2.924 | 0.38 |
| AFP | −1.036 | 0.355 | 0.135–0.934 | 0.04 |
| CEA | −0.060 | 0.941 | 0.459–1.933 | 0.87 |
| CA199 | −0.592 | 0.553 | 0.211–1.452 | 0.23 |
| SATA | −0.007 | 0.993 | 0.985–1.001 | 0.10 |
| IATA | 0.093 | 1.098 | 1.002–1.202 | 0.04 |
AFP, alpha-fetoprotein; CA199, carbohydrate antigen 199; CEA, carcinoembryonic antigen; CI, confidence interval; IATA, intramuscular adipose tissue area; LVI, lymphovascular invasion; N, node; OR, odds ratio; PNI, perineural invasion; SATA, subcutaneous adipose tissue area; T, tumor.
The predictive performance of single parameter and multi-parameter combinations are shown in Table 5 and Figure 3. In the single-factor analysis, the N stage had the highest AUC of 0.673. The AUC of SATA and IATA was 0.600 and 0.616, respectively, while the AUC of combined SATA and IATA was 0.687, slightly higher than that of the N stage. The combination of all preoperative factors (sex, age, CEA, AFP, CA199, SATA and IATA, AUC =0.719) showed similar predictive performance with pathological factors (N stage, T stage, cell grade, LVI and PNI, AUC =0.732).
Table 5
| Factors | AUC | 95% CI | P |
|---|---|---|---|
| N stage + T stage + Cell grade + LVI + PNI | 0.732 | 0.666–0.798 | <0.001 |
| Sex + Age + CEA + AFP + CA199 + SATA + IATA | 0.719 | 0.652–0.787 | <0.001 |
| SATA + IATA | 0.687 | 0.621–0.754 | <0.001 |
| N stage | 0.673 | 0.604–0.743 | <0.001 |
| Cell grade | 0.668 | 0.600–0.736 | <0.001 |
| T stage | 0.642 | 0.574–0.710 | <0.001 |
| LVI | 0.620 | 0.546–0.695 | 0.002 |
| IATA | 0.616 | 0.541–0.690 | 0.002 |
| Sex | 0.608 | 0.539–0.677 | 0.005 |
| Age, years | 0.602 | 0.529–0.675 | 0.008 |
| SATA | 0.600 | 0.526–0.674 | 0.009 |
| PNI | 0.582 | 0.508–0.656 | 0.03 |
| CEA | 0.570 | 0.494–0.646 | 0.07 |
| AFP | 0.555 | 0.478–0.633 | 0.15 |
| CA199 | 0.549 | 0.471–0.626 | 0.20 |
AFP, alpha-fetoprotein; AUC, area under the curve; CA199, carbohydrate antigen 199; CEA, carcinoembryonic antigen; CI, confidence interval; IATA, intramuscular adipose tissue area; LVI, lymphovascular invasion; N, node; PNI, perineural invasion; SATA, subcutaneous adipose tissue area; T tumor.
Discussion
In this retrospective study, we found that the IATA was an independent risk factor for the occurrence of liver metastasis in GC patients undergoing radical gastrectomy. The ROC curve showed that the combination of SATA and IATA had an ideal predictive performance.
One previous study found that patients with venous/lymphatic invasion, pathological stage IV (especially combined with T4 stage), intestinal Lauren type, and combined elevation of CEA and CA199 were prone to liver metastasis after radical gastrectomy (12). Besides, Kumagai et al. reported that the lymphatic system invasion was closely related to the occurrence of liver metastasis in GC patients (13). In the present study, we also found higher T and N stages as well as increased LVI and PNI in the liver metastasis group. However, these factors can only be obtained after the surgery. Although tumor markers including CEA, CA199, and AFP can be tested before the surgery, the proportion of abnormalities was less than 40% in this study. Therefore, there is an urgent clinical need for a reliable and noninvasive method that can assess the risk factors of postoperative liver metastasis for GC patients.
Abdominal CT image at the L3 level was widely applied to evaluate the body composition for diagnosing myosteatosis (14-17). Some studies have shown that myosteatosis was related to the prognosis of gastrointestinal tumors (11,18). Murnane et al. found that in patients undergoing radical esophageal and GC surgery, myosteatosis was associated with a significantly increased risk of overall and severe complications as well as substantially reduced long-term survival (11). Some other studies also reported similar results in other gastrointestinal tumors such as ampullary cancer (19), pancreatic cancer (20,21), and colorectal cancer (22-26). In this study, there was no statistical difference in SMA, while there were statistical differences in IATA and SATA between the two groups. These could be explained by gender and age differences between the two groups. Males usually had more muscle content than females while muscle mass would reduce with increasing age, and in the present study, the liver metastasis group included more males (86% vs. 64%, P<0.001) and had a higher mean age (60.9 vs. 57.07 years, P=0.004). In addition, the liver metastasis group had a larger IATA. Increased IAT is one of the manifestations of muscle atrophy. Therefore, increased IAT may be more sensitive than reduced muscle mass in the early stage of GC. In summary, for patients with increased IAT, early intervention should be considered for the possible occurrence of liver metastasis.
In addition, we found that SATA was smaller in the liver metastasis group. Cancer is a consumptive disease. Several studies have confirmed that patients with more subcutaneous adipose tissue tended to have a better prognosis (27-29). Therefore, the more subcutaneous adipose tissue indicated a better nutritional state of cancer patients, allowing them to resist energy consumption resulting from tumors.
Although the AUC of SATA or IATA alone was lower than that of the N stage, the AUC of the combined SATA and IATA was up to 0.687, slightly higher than that of the N stage with 0.673. Furthermore, SATA and IATA could be measured with preoperative CT images, but the N stage can only be obtained with the postoperative pathology. At present, N staging has been widely used in the evaluation of tumor prognosis. Furthermore, we found that the combination of all significant preoperative factors (sex, age, CEA, AFP, CA199, SATA and IATA, AUC =0.719) showed similar predictive performance with combined pathological factors (N stage, T stage, cell grade, LVI and PNI, AUC =0.732). Therefore, body composition parameters showed potential application value in clinical practice.
Our study has several limitations. Firstly, this was a retrospective study conducted in a single institution; there may be potential selection biases. Secondly, the number of female patients included in this study was relatively few, and our data needed to be further verified in a larger sample size. Thirdly, it was difficult to eliminate the errors between the manually outlined muscle area and the actual situation. Fourthly, we did not take adjuvant therapy as an indicator, because treatment methods varied in different patients, which also required a larger sample size.
Conclusions
The preoperative SATA and IATA at the L3 level were significant predictors of postoperative liver metastasis in GC patients undergoing radical gastrectomy. The combination of SATA and IATA showed similar predictive efficacy to the N stage for the occurrence of liver metastasis after radical gastrectomy.
Acknowledgments
None.
Footnote
Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-82/rc
Data Sharing Statement: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-82/dss
Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-82/prf
Funding: This study was supported by
Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-82/coif). The authors have no conflicts of interest to declare.
Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study protocol was approved by the Institutional Ethics Review Committee of The Affiliated Cancer Hospital of Nanjing Medical University (Jiangsu Cancer Hospital) (No. 2023ke-kuai055-GZ-01) before the study was initiated. Due to the retrospective nature of the study, and individual consent was not required.
Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
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