Predictive value of preoperative subcutaneous and intramuscular adipose tissue for the occurrence of postoperative liver metastasis in gastric cancer patients undergoing radical gastrectomy
Original Article

Predictive value of preoperative subcutaneous and intramuscular adipose tissue for the occurrence of postoperative liver metastasis in gastric cancer patients undergoing radical gastrectomy

Di Dai1# ORCID logo, Zhengyuan Bao2#, Yinsu Zhu1, Meiqin Wang1

1Department of Radiology, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, Nanjing, China; 2Division of Sports Medicine and Adult Reconstructive Surgery, Department of Orthopedic Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China

Contributions: (I) Conception and design: D Dai, M Wang; (II) Administrative support: Y Zhu; (III) Provision of study materials or patients: D Dai, M Wang; (IV) Collection and assembly of data: D Dai; (V) Data analysis and interpretation: D Dai, Z Bao; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

#These authors contributed equally to this work.

Correspondence to: Yinsu Zhu, MD; Meiqin Wang, MM. Department of Radiology, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, 42 Baiziting, Nanjing 210009, China. Email: zhuyinsu@njmu.edu.cn; meiqin-wang@163.com.

Background: Body compositions were associated with the clinical outcomes of patients with malignant tumors. Our study aimed to explore the predictive value of preoperative body compositions for liver metastasis after radical gastrectomy in gastric cancer (GC).

Methods: GC patients undergoing radical gastrectomy in the single center from January 2012 to December 2023 were retrospectively included. Patients with distant metastases or other malignant tumors before the surgery were excluded. Included patients were divided into the liver metastasis and control groups according to the presence of liver metastasis within the 3-year follow-up. Body compositions including skeletal muscle (SM), visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and intramuscular adipose tissue (IAT) were estimated using preoperative computed tomography (CT) images at the L3 level. Multivariate logistic regression analysis was used to identify the independent risk factors of liver metastasis. Receiver operating characteristic curve was used to evaluate the predictive performance of significant factors.

Results: A total of 300 patients were included for the final analysis with 223 in the control group and 77 in the liver metastasis group. Compared with the control group, the liver metastasis group contained more males (P<0.001), presented older age (P=0.004), higher T and N stages (P<0.001 for both), higher incidence of moderately-poorly and poorly differentiated cell grade (P<0.001), increased lymphovascular and perineural invasions (P<0.001 and P=0.01, respectively), higher incidence of abnormal carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199) and alpha-fetoprotein (AFP) (P=0.01, 0.01 and 0.003, respectively), smaller SAT area (SATA) (P=0.009) and larger IAT area (IATA) (P=0.002). Multivariate logistic regression analysis demonstrated that the 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. The combination of SATA and IATA exhibited good predictive performance for liver metastasis [area under the curve (AUC) =0.687, 95% confidence interval (CI): 0.621–0.754].

Conclusions: The preoperative SATA and IATA at the L3 level were significant predictors of postoperative liver metastasis in GC patients undergoing radical gastrectomy.

Keywords: Gastric cancer (GC); liver metastasis; subcutaneous adipose tissue (SAT); intramuscular adipose tissue (IAT)


Submitted Feb 04, 2025. Accepted for publication Apr 29, 2025. Published online Jun 26, 2025.

doi: 10.21037/jgo-2025-82


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).

Figure 1 Flowchart of patient selection and grouping. CT, computed tomography.

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.

Figure 2 Body composition assessment with CT using SliceOmatic software. (A) Liver metastasis group with original CT image; (B) control group with original CT image; (C) liver metastasis group with tagged CT image; (D) control group with tagged CT image. Within the tagged figure, skeletal muscle area was measured with a threshold set at −29 to +150 HU (violet), visceral adipose tissue area at −150 to −50 HU (red), subcutaneous adipose tissue area and intramuscular adipose tissue area at −190 to −30 HU (green and blue, respectively). CT, computed tomography; HU, Hounsfield unit.

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

Patient baseline and tumor characteristics

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

Patient body composition data

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

Interobserver reliability

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

Logistic regression analysis for postoperative liver metastasis

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

The predictive performance of single parameter and multi-parameter combination

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.

Figure 3 The predictive performance of single parameter and multi-parameter combinations via ROC curve analysis. AFP, alpha-fetoprotein; CA199, carbohydrate antigen 199; CEA, carcinoembryonic antigen; IATA, intramuscular adipose tissue area; LVI, lymphovascular invasion; N, node; PNI, perineural invasion; ROC, receiver operating characteristic; 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 the Jiangsu Institute of Cancer Research (No. ZL202312).

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/.


References

  1. Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 2024;74:229-63. [Crossref] [PubMed]
  2. Zhang K, Chen L. Chinese consensus on the diagnosis and treatment of gastric cancer with liver metastases. Ther Adv Med Oncol 2020;12:1758835920904803. [Crossref] [PubMed]
  3. Xiao Y, Zhang B, Wu Y. Prognostic analysis and liver metastases relevant factors after gastric and hepatic surgical treatment in gastric cancer patients with metachronous liver metastases: a population-based study. Ir J Med Sci 2019;188:415-24. [Crossref] [PubMed]
  4. Petrelli F, Coinu A, Cabiddu M, et al. Hepatic resection for gastric cancer liver metastases: A systematic review and meta-analysis. J Surg Oncol 2015;111:1021-7. [Crossref] [PubMed]
  5. Malietzis G, Aziz O, Bagnall NM, et al. The role of body composition evaluation by computerized tomography in determining colorectal cancer treatment outcomes: a systematic review. Eur J Surg Oncol 2015;41:186-96. [Crossref] [PubMed]
  6. Boshier PR, Heneghan R, Markar SR, et al. Assessment of body composition and sarcopenia in patients with esophageal cancer: a systematic review and meta-analysis. Dis Esophagus 2018; [PubMed]
  7. Londhe P, Guttridge DC. Inflammation induced loss of skeletal muscle. Bone 2015;80:131-42. [Crossref] [PubMed]
  8. Waki Y, Irino T, Makuuchi R, et al. Impact of Preoperative Skeletal Muscle Quality Measurement on Long-Term Survival After Curative Gastrectomy for Locally Advanced Gastric Cancer. World J Surg 2019;43:3083-93. [Crossref] [PubMed]
  9. Tolonen A, Pakarinen T, Sassi A, et al. Methodology, clinical applications, and future directions of body composition analysis using computed tomography (CT) images: A review. Eur J Radiol 2021;145:109943. [Crossref] [PubMed]
  10. Fang Z, Du F, Shang L, et al. CT assessment of preoperative nutritional status in gastric cancer: severe low skeletal muscle mass and obesity-related low skeletal muscle mass are unfavorable factors of postoperative complications. Expert Rev Gastroenterol Hepatol 2021;15:317-24. [Crossref] [PubMed]
  11. Murnane LC, Forsyth AK, Koukounaras J, et al. Myosteatosis predicts higher complications and reduced overall survival following radical oesophageal and gastric cancer surgery. Eur J Surg Oncol 2021;47:2295-303. [Crossref] [PubMed]
  12. Song JC, Ding XL, Zhang Y, et al. Prospective and prognostic factors for hepatic metastasis of gastric carcinoma: A retrospective analysis. J Cancer Res Ther 2019;15:298-304. [Crossref] [PubMed]
  13. Kumagai K, Tanaka T, Yamagata K, et al. Liver metastasis in gastric cancer with particular reference to lymphatic advancement. Gastric Cancer 2001;4:150-5. [Crossref] [PubMed]
  14. McGovern J, Dolan RD, Horgan PG, et al. Computed tomography-defined low skeletal muscle index and density in cancer patients: observations from a systematic review. J Cachexia Sarcopenia Muscle 2021;12:1408-17. [Crossref] [PubMed]
  15. Ohara M, Suda G, Kimura M, et al. Analysis of the optimal psoas muscle mass index cut-off values, as measured by computed tomography, for the diagnosis of loss of skeletal muscle mass in Japanese people. Hepatol Res 2020;50:715-25. [Crossref] [PubMed]
  16. Denbo JW, Kim BJ, Vauthey JN, et al. Overall Body Composition and Sarcopenia Are Associated with Poor Liver Hypertrophy Following Portal Vein Embolization. J Gastrointest Surg 2021;25:405-10. [Crossref] [PubMed]
  17. Taki Y, Sato S, Nakatani E, et al. Preoperative skeletal muscle index and visceral-to-subcutaneous fat area ratio are associated with long-term outcomes of elderly gastric cancer patients after gastrectomy. Langenbecks Arch Surg 2021;406:463-71. [Crossref] [PubMed]
  18. Fang T, Gong Y, Wang Y. Prognostic values of myosteatosis for overall survival in patients with gastric cancers: A meta-analysis with trial sequential analysis. Nutrition 2023;105:111866. [Crossref] [PubMed]
  19. Van Rijssen LB, van Huijgevoort NC, Coelen RJ, et al. Skeletal Muscle Quality is Associated with Worse Survival After Pancreatoduodenectomy for Periampullary, Nonpancreatic Cancer. Ann Surg Oncol 2017;24:272-80. [Crossref] [PubMed]
  20. Stretch C, Aubin JM, Mickiewicz B, et al. Sarcopenia and myosteatosis are accompanied by distinct biological profiles in patients with pancreatic and periampullary adenocarcinomas. PLoS One 2018;13:e0196235. [Crossref] [PubMed]
  21. van Dijk DP, Bakens MJ, Coolsen MM, et al. Low skeletal muscle radiation attenuation and visceral adiposity are associated with overall survival and surgical site infections in patients with pancreatic cancer. J Cachexia Sarcopenia Muscle 2017;8:317-26. [Crossref] [PubMed]
  22. Sueda T, Takahasi H, Nishimura J, et al. Impact of Low Muscularity and Myosteatosis on Long-term Outcome After Curative Colorectal Cancer Surgery: A Propensity Score-Matched Analysis. Dis Colon Rectum 2018;61:364-74. [Crossref] [PubMed]
  23. Margadant CC, Bruns ER, Sloothaak DA, et al. Lower muscle density is associated with major postoperative complications in older patients after surgery for colorectal cancer. Eur J Surg Oncol 2016;42:1654-9. [Crossref] [PubMed]
  24. Brown JC, Caan BJ, Meyerhardt JA, et al. The deterioration of muscle mass and radiodensity is prognostic of poor survival in stage I-III colorectal cancer: a population-based cohort study (C-SCANS). J Cachexia Sarcopenia Muscle 2018;9:664-72. [Crossref] [PubMed]
  25. Kroenke CH, Prado CM, Meyerhardt JA, et al. Muscle radiodensity and mortality in patients with colorectal cancer. Cancer 2018;124:3008-15. [Crossref] [PubMed]
  26. Martin L, Hopkins J, Malietzis G, et al. Assessment of Computed Tomography (CT)-Defined Muscle and Adipose Tissue Features in Relation to Short-Term Outcomes After Elective Surgery for Colorectal Cancer: A Multicenter Approach. Ann Surg Oncol 2018;25:2669-80. [Crossref] [PubMed]
  27. Antoun S, Bayar A, Ileana E, et al. High subcutaneous adipose tissue predicts the prognosis in metastatic castration-resistant prostate cancer patients in post chemotherapy setting. Eur J Cancer 2015;51:2570-7. [Crossref] [PubMed]
  28. Makrakis D, Rounis K, Tsigkas AP, et al. Effect of body tissue composition on the outcome of patients with metastatic non-small cell lung cancer treated with PD-1/PD-L1 inhibitors. PLoS One 2023;18:e0277708. [Crossref] [PubMed]
  29. Ebadi M, Martin L, Ghosh S, et al. Subcutaneous adiposity is an independent predictor of mortality in cancer patients. Br J Cancer 2017;117:148-55. [Crossref] [PubMed]
Cite this article as: Dai D, Bao Z, Zhu Y, Wang M. Predictive value of preoperative subcutaneous and intramuscular adipose tissue for the occurrence of postoperative liver metastasis in gastric cancer patients undergoing radical gastrectomy. J Gastrointest Oncol 2025;16(3):865-874. doi: 10.21037/jgo-2025-82

Download Citation