Retrospective Study Open Access
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Surg. Jul 27, 2024; 16(7): 2145-2156
Published online Jul 27, 2024. doi: 10.4240/wjgs.v16.i7.2145
Correlation between abdominal computed tomography signs and postoperative prognosis for patients with colorectal cancer
Shao-Min Yang, Department of Radiology, Xingtan Hospital Affiliated to Shunde Hospital of Southern Medical University, Foshan 528315, Guangdong Province, China
Jie-Mei Liu, Department of Rehabilitation Medicine, Shunde Hospital, Southern Medical University, Foshan 528399, Guangdong Province, China
Rui-Ping Wen, Yu-Dong Qian, Jing-Song Sun, Department of Radiology, Lecong Hospital of Shunde, Foshan 528315, Guangdong Province, China
Jing-Bo He, Department of Ultrasound, Lecong Hospital of Shunde, Foshan 528315, Guangdong Province, China
ORCID number: Shao-Min Yang (0009-0006-3817-3785); Jie-Mei Liu (0009-0000-8806-1008); Rui-Ping Wen (0009-0002-1672-9050); Yu-Dong Qian (0009-0000-6139-3504); Jing-Bo He (0009-0003-7147-3729); Jing-Song Sun (0009-0004-2835-6604).
Co-first authors: Shao-Min Yang and Jie-Mei Liu.
Co-corresponding authors: Jing-Bo He and Jing-Song Sun.
Author contributions: Yang SM and Liu JM contributed equally to this work, and they designed the manuscript; Wen RP and Qian YD organized the clinical data; He JB and Sun JS contributed equally to this work as the co-corresponding authors of this manuscript, and they analyzed the data, prepared the figures, and supervised this study.
Institutional review board statement: The study was reviewed and approved by the Xingtan Hospital Affiliated to Shunde Hospital of Southern Medical University Institutional Review Board.
Informed consent statement: The Institutional Review Board approved the exemption from informed consent.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: The data used in this study can be obtained from the corresponding author upon request.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Jing-Bo He, MBBS, Attending Doctor, Department of Ultrasound, Lecong Hospital of Shunde, No. 45 Lecong Avenue, Lecong Town, Shunde District, Foshan 528315, Guangdong Province, China. bo1221sun@163.com
Received: April 3, 2024
Revised: May 8, 2024
Accepted: May 27, 2024
Published online: July 27, 2024
Processing time: 109 Days and 21.6 Hours

Abstract
BACKGROUND

Patients with different stages of colorectal cancer (CRC) exhibit different abdominal computed tomography (CT) signs. Therefore, the influence of CT signs on CRC prognosis must be determined.

AIM

To observe abdominal CT signs in patients with CRC and analyze the correlation between the CT signs and postoperative prognosis.

METHODS

The clinical history and CT imaging results of 88 patients with CRC who underwent radical surgery at Xingtan Hospital Affiliated to Shunde Hospital of Southern Medical University were retrospectively analyzed. Univariate and multivariate Cox regression analyses were used to explore the independent risk factors for postoperative death in patients with CRC. The three-year survival rate was analyzed using the Kaplan-Meier curve, and the correlation between postoperative survival time and abdominal CT signs in patients with CRC was analyzed using Spearman correlation analysis.

RESULTS

For patients with CRC, the three-year survival rate was 73.86%. The death group exhibited more severe characteristics than the survival group. A multivariate Cox regression model analysis showed that body mass index (BMI), degree of periintestinal infiltration, tumor size, and lymph node CT value were independent factors influencing postoperative death (P < 0.05 for all). Patients with characteristics typical to the death group had a low three-year survival rate (log-rank χ2 = 66.487, 11.346, 12.500, and 27.672, respectively, P < 0.05 for all). The survival time of CRC patients was negatively correlated with BMI, degree of periintestinal infiltration, tumor size, lymph node CT value, mean tumor long-axis diameter, and mean tumor short-axis diameter (r = -0.559, 0.679, -0.430, -0.585, -0.425, and -0.385, respectively, P < 0.05 for all). BMI was positively correlated with the degree of periintestinal invasion, lymph node CT value, and mean tumor short-axis diameter (r = 0.303, 0.431, and 0.437, respectively, P < 0.05 for all).

CONCLUSION

The degree of periintestinal infiltration, tumor size, and lymph node CT value are crucial for evaluating the prognosis of patients with CRC.

Key Words: Colorectal cancer; Abdominal; Computed tomography signs; Radical surgery; Prognosis; Correlation

Core Tip: The incidence and mortality rates of colorectal cancer (CRC) are alarming. We analyzed the demographic data, pathological information, and abdominal computed tomography (CT) findings of 88 patients with CRC after radical surgery. This is a retrospective single-center study to investigate the correlation of demographic data, pathological information, and abdominal CT signs with prognosis. We solved the problem of CRC prognosis assessment by observing the changes in the survival rate of patients with CRC under different influencing factors.



INTRODUCTION

Malignant tumors include carcinoma, sarcoma, and carcinosarcoma, which are caused by malignant cell proliferation and are invasive and capable of metastasis. Malignant tumors have become the leading killer of human health[1]. Mutations or abnormal expression of genes cause cells to acquire the ability to maintain proliferation signal transduction, escape growth inhibitors, resist cell death, replicate immortality, induce angiogenesis, and activate invasion and metastasis, leading to tumor occurrence and progression[2].

A common malignant tumor worldwide is colorectal cancer (CRC), and in China, its incidence and mortality rates are increasing[3]. Among the malignant tumors prevalent in China, the mortality rate of CRC ranks second only to stomach, lung, liver, and esophageal cancers. Surgical resection of tumors is currently the primary method used to treat CRC. However, only 20% of patients treated with resection and adjuvant therapy are cured, and 20%-25% of patients newly diagnosed with CRC annually have metastasis or metastatic diseases[4]. In addition, the five-year survival rate of patients with advanced colon cancer in China is only 10.8%, and approximately 50% of the patients die as a result of local recurrence or metastasis after surgery[5]. Therefore, the accurate assessment of CRC prognoses is crucial for guiding clinical interventions and optimizing treatment outcomes. Currently, clinical research is focused on searching for the factors that may affect prognosis after radical CRC surgery. However, the clinicopathological features and prognosis of patients with different stages of CRC exhibit different abdominal computed tomography (CT) signs, which affect the treatment of CRC[6]. Consequently, it is not reasonable to treat CRC patients with different abdominal CT signs using the same regimen. Studies have pointed out that the clinicopathological features and prognosis of CRC patients with different abdominal CT signs differ[7].

Thus, this study aimed to analyze the correlation between abdominal CT signs and postoperative prognosis of patients with CRC and clarify the impact of abdominal CT signs on the short-term prognosis of patients to provide new ideas for early prognosis prediction of CRC and guiding clinicians to identify high-risk patients and take countermeasures to improve the prognosis of CRC.

MATERIALS AND METHODS
Patient selection

A retrospective study was conducted on 88 patients with CRC who underwent radical surgery at Xingtan Hospital Affiliated to Shunde Hospital of Southern Medical University from January 2020 to December 2020. The patient selection criteria were as follows. All patients: (1) Were diagnosed with CRC in accordance with the Guidelines for the Diagnosis and Treatment of Colorectal Cancer (2010 Edition), which was confirmed via pathological examination[8]; (2) Underwent radical surgery; and (3) Had no history of radiotherapy or chemotherapy. Patients were excluded if: (1) They had other acute/chronic liver and kidney dysfunction or malignant tumors; (2) They had heart dysfunction or congenital heart disease; or (3) Their follow-up information was incomplete.

Clinical data collection

The baseline data for all the patients were collected. These data included: (1) Demographic data: Age, sex, body mass index (BMI), smoking history, and drinking history; (2) Pathological information: Pathological stage, vascular thrombus, degree of tumor differentiation, lymph node metastasis, and tumor location; and (3) Abdominal CT signs: The form of intestinal wall thickening, degree of periintestinal infiltration, transformation rate of signal, low-density area after enhancement, lymph node location, tumor size, lymph node CT value, mean tumor long-axis diameter, and mean tumor short-axis diameter.

Preoperative abdominal CT scan

Intestinal preparation: The patients were required to adhere to a diet with less residue 2 d before the examination, eat liquid food the day before, take 50 g of purgative 50% magnesium sulfate twice the night before the examination, drink more water, and record the timing of their defecations. Ten minutes before the CT scan, 20 mg of the antispasmolytic drug amidoamine hydrochloride was administered intramuscularly to relieve intestinal spasms, reduce colonic tension, and decrease intestinal peristaltic artifacts. The patient was placed in the right lateral decubitus position, and air was injected through a rectal catheter. Next, the patient was placed in a supine or prone position, and additional air was injected. The volume of air injected was 1000-1500 mL, depending on the patient’s tolerance.

CT scanning: A 128-row spiral CT scan was performed. The parameters are as follows: Tube voltage of 120 kVp, tube current of 250 mA, pitch of 0.969, rotation time of 0.75 s, reconstruction interval of 5 mm, layer thickness of 5 mm, and matrix of 512 × 512. During the scan, the patient was placed in a supine position to enable the observation of the inflated status of the colon and rectum. Then, the nonionic contrast agent Ornepiac was quickly injected into the anterior cubital vein with a high-pressure syringe at a dose of 1.5 mL/kg and an injection speed of 2.5-3.0 mL/s. Subsequently, arterial phase, portal vein phase, and delayed phase scans were performed at 23 s, 50 s, and 180 s, respectively. The thickness, reconstruction interval, and pitch were 3.0 mm, 1.5 mm, and 2.0, respectively. The scanning area was the entire colon and liver.

Image processing: Two senior imaging physicians used EBW4.5 to evaluate the imaging features of the lesions without knowing the results of the pathological diagnoses. If the two physicians had different opinions, a consensus was reached through negotiation. The plain scan and enhanced CT values of the solid components of the lesions were measured, and the same region of interest was evaluated at each stage while avoiding areas corresponding to phenomena such as calcification, bleeding, and necrosis fibrosis. The average of the results measured by the two physicians was used as the final result.

Grouping

The survival rate of the patients at three years after their operations was determined. The end of the follow-up period was December 2023 or the date of death, whichever occurred first for a given patient. Survivors were included in the “survival” group, and the deceased were included in the “death” group.

Statistical analysis

The data were processed using SPSS version 23.0. Measurement data are expressed as the mean ± SD. Count data are expressed as percentages (%) and were compared using a χ2 test (used when the theoretical frequency is greater than 5) or an exact test (used when the theoretical frequency is less than 5). Multivariate Cox regression was used to analyze the factors affecting the death of patients with CRC three years after their surgeries. The sensitivity and specificity of the independent influencing factors were analyzed using the receiver operating characteristic (ROC) curve. We analyzed the three-year survival of patients according to the degree of periintestinal infiltration, tumor size, lymph node CT value, and BMI using the Kaplan–Meier curve and the log-rank test. The Spearman correlation test was used to evaluate the correlation between non-normal measurement data and rank data. The level of statistical significance was set at P < 0.05.

RESULTS
Prognosis and abdominal CT signs of patients

During the three-year follow-up period, 65 of the 88 patients with CRC survived, and 23 died. Hence, the survival rate was 73.86%, and the mortality rate was 26.14%. In 15, 37, 30, and 6 cases, the form of intestinal wall thickening was polyps or cauliflower, eccentric, uneven ring, and uniform ring, respectively. In 33, 31, and 24 cases, the degree of periintestinal infiltration was mild, moderate, and severe, respectively. In 30, 34, and 24 cases, the degree of enhancement was mild, moderate, and severe, respectively. The number of cases with a low-density area after enhancement was 53. In 51, 29, and 8 cases, the lymph node location was the mesenterium, root, and lateral position, respectively. The mean tumor size was 3.95 ± 1.95 cm, the mean lymph node CT value was 27.23 ± 10.11 HU, the mean tumor long-axis diameter was 0.65 ± 0.38 cm, and the mean tumor short-axis diameter was 0.43 ± 0.28 cm. Figures 1 and 2 show the patients’ CT scans.

Figure 1
Figure 1 Computed tomography image of a 44-year-old male patient with colorectal cancer. A: Plain computed tomography (CT) scan. The wall of the left descending colon (lower pole region of the flat kidney) was thickened circularly, and a soft tissue mass (indicated by the orange arrow) was observed. The density of the mass was similar to that of the muscle. The CT value was approximately 48 HU; B: Enhanced CT. The density of the mass was higher than that of the muscle, the CT value was approximately 68 HU, a weak enhancement area was seen in the mass (indicated by the orange arrow), the fat layer around the mass was blurred with enhancement (indicated by the yellow arrow), and the lateral vertebral fascia was thickened and enhanced (indicated by the blue arrow). The images also show that the patient’s proximal bowel duct was dilated.
Figure 2
Figure 2 Computed tomography image of a 63-year-old female patient with colorectal cancer. A: Plain computed tomography (CT) scan. The wall of the upper rectum was eccentrically thickened, and the CT value of the soft tissue mass was approximately 42 HU; B: Enhanced CT. The blurring of fat in the mesorectum and enhancement of the cord (indicated by the orange arrow) closest to the rectal fascia were approximately 5 mm away (indicated by the yellow arrow).
Univariate analysis of postoperative death

Compared with the survival group, the death group was more likely to have a BMI > 24 kg/m2, pathological stage IV, highly differentiated tumor, severe periintestinal infiltration, tumor size ≥ 4 cm, lymph node CT value ≥ 30 HU, mean tumor long-axis diameter ≥ 0.6 cm, and mean tumor short-axis diameter ≥ 0.45 cm (P < 0.05 for all), as shown in Table 1.

Table 1 Univariate analysis of postoperative death in patients with colorectal cancer, n (%).
Data

Death group (n = 23)
Survival group (n = 65)
χ2
P value
GenderMale14 (60.87)37 (56.92)0.1090.742
Female9 (39.13)28 (43.08)
Age≥ 60 years15 (65.22)36 (55.38)0.6740.412
< 60 years8 (34.78)29 (44.62)
BMI< 18.5 kg/m20 (0.00)4 (6.15)16.992< 0.001
18.5-24 kg/m211 (47.83)55 (84.62)
> 24 kg/m212 (52.17)6 (9.23)
Smoking history Yes9 (39.13)23 (35.38)0.1030.748
No14 (60.87)42 (64.62)
Drinking history Yes7 (30.43)18 (27.69)0.0630.802
No16 (69.57)47 (72.31)
Pathological stage I0 (0.00)10 (15.38)15.4010.001
II7 (30.43)39 (60.00)
III12 (52.17)13 (20.00)
IV4 (17.39)3 (4.62)
Blood vessel invasionYes1 (4.35)2 (3.08)< 0.001> 0.999
No22 (95.65)63 (96.92)
Degree of tumor differentiation Poorly differentiated6 (26.09)5 (7.69)8.9500.011
Moderately differentiated16 (69.57)42 (64.62)
Highly differentiated1 (4.35)18 (27.69)
Lymphatic metastasisYes10 (43.48)14 (21.54)4.1230.042
No13 (56.52)51 (78.46)
Tumor siteRight semicolon8 (34.78)12 (18.46)2.8240.244
Left semicolon5 (21.74)14 (21.54)
Rectum10 (43.48)39 (60.00)
Intestinal wall thickening formPolyps or cauliflower thickening6 (26.09)9 (13.85)2.2010.532
Eccentric thickening9 (39.13)28 (43.08)
Uneven ring thickening6 (26.09)24 (36.92)
Uniform ring thickening2 (8.70)4 (6.15)
Degree of periintestinal infiltrationMild0 (0.00)33 (50.77)48.385< 0.001
Moderate4 (17.39)27 (41.54)
Severe19 (82.61)5 (7.69)
Transformation rate of signalMild8 (34.78)22 (33.85)2.8790.237
Moderate6 (26.09)28 (43.08)
Severe9 (39.13)15 (23.08)
Low-density area after enhancementYes13 (56.52)40 (61.54)0.1780.673
No10 (43.48)25 (38.46)
Lymph node locationMesenterium15 (65.22)36 (55.38)1.2340.540
Root7 (30.43)22 (33.85)
Lateral1 (4.35)7 (10.77)
Tumor size< 4 cm4 (17.39)38 (58.46)11.4860.001
≥ 4 cm19 (82.61)27 (41.54)
Lymph node CT value < 30 HU4 (17.39)39 (60.00)10.6970.001
≥ 30 HU19 (82.61)26 (40.00)
Mean tumor long-axis diameter< 0.6 cm4 (17.39)35 (53.85)7.7310.005
≥ 0.6 cm19 (82.61)30 (46.15)
Mean tumor short-axis diameter< 0.45 cm5 (21.74)36 (55.38)7.7290.005
≥ 0.45 cm18 (78.26)29 (44.62)
Multivariate Cox regression analysis of postoperative death

Using the postoperative prognosis of the patients with CRC as the dependent variable (0 = survival, 1 = death), and the statistically significant indicators in the univariate analysis (BMI, pathological stage, degree of intestinal infiltration, tumor size, lymph node CT value, mean tumor long-axis diameter, and mean tumor short-axis diameter) as independent variables (Table 2), multivariate Cox regression analysis demonstrated that BMI, degree of periintestinal infiltration, tumor size, and lymph node CT value were independent factors influencing the likelihood of postoperative death in CRC patients (P < 0.05), as shown in Table 3. ROC curve analysis showed that both BMI and tumor size had the highest sensitivity of 82.6%. The specificity of BMI and degree of periintestinal infiltration was also higher at 83.1% and 86.2%, respectively (Table 4 and Figure 3).

Figure 3
Figure 3 Receiver operating characteristic curve analysis for sensitivity and specificity. BMI: Body mass index; CT: Computed tomography.
Table 2 Assignment table.
Independent variable
Assignment
BMI0: < 18.5 kg/m2; 1: 18.5-24 kg/m2; 2: > 24 kg/m2
Pathological stage1: I; 2: II; 3: III; 4: IV
Degree of tumor differentiation1: Poorly differentiated; 2: Moderately differentiated; 3: Highly differentiated
Degree of periintestinal infiltration1: Mild; 2: Moderate; 3: Severe
Tumor size0: < 4 cm; 1: ≥ 4 cm
Lymph node CT value0: < 30 HU; 1: ≥ 30 HU
Mean tumor long-axis diameter0: < 0.6 cm; 1: ≥ 0.6 cm
Mean tumor short-axis diameter0: < 0.45 cm; 1: ≥ 0.45 cm
Table 3 Multivariate Cox regression analysis of postoperative death in patients with colorectal cancer.
Independent variable
B
SE
Wald
P value
OR
95%CI
BMI0.4090.1398.6210.0031.5061.146-1.979
Pathological stage2.2550.521
I-7.741222.3690.0010.9720.0000.000-8.303
II0.9570.7801.5040.2202.6030.564-12.003
III1.0520.7122.1830.1402.8650.709-11.569
Degree of tumor differentiation1.7490.417
Poorly differentiated0.6861.2900.2830.5951.9860.158-24.909
Moderately differentiated-0.3021.1140.0740.7860.7390.083-6.565
Degree of periintestinal infiltration7.0300.030
Mild-12.450167.4680.0060.9410.0000.000-1.390
Moderate-1.7840.6737.0250.0080.1680.045-0.628
Tumor size1.5220.6605.3220.0214.5811.257-16.691
Lymph node CT value1.3620.6893.9110.0483.9041.012-15.059
Mean tumor long-axis diameter0.9180.8091.2870.2572.5050.513-12.240
Table 4 Receiver operating characteristic analysis.
Variable
Area (95%CI)
Standard error
P value
Sensitivity
Specificity
BMI0.847 (0.753-0.942)0.048< 0.00182.6%83.1%
Degree of periintestinal infiltration0.735 (0.613-0.857)0.0620.00152.2%86.2%
Tumor size0.705 (0.587-0.824)0.060.00482.6%58.5%
Lymph node CT value0.648 (0.518-0.778)0.0660.03669.6%60.0%
CRC survival rate analyzed by Kaplan-Meier curve

During the three-year follow-up period, it was found that patients with severe periintestinal infiltration (log-rank χ2 = 66.487, P < 0.001), tumor size ≥ 4 cm (log-rank χ2 = 11.346, P = 0.001), lymph node CT value ≥ 30 HU (log-rank χ2 = 12.500, P < 0.001), or BMI > 24 kg/m2 (log-rank χ2 = 27.672, P < 0.001) had a lower survival rate, as shown in Figure 4.

Figure 4
Figure 4 Kaplan-Meier curve. A: Degree of periintestinal infiltration; B: Tumor size; C: Lymph node computed tomography value; D: Body mass index. BMI: Body mass index; CT: Computed tomography.
Correlation analysis of postoperative survival time and abdominal CT signs in patients with CRC

The survival time of patients with CRC was negatively correlated with BMI, degree of periintestinal infiltration, tumor size, lymph node CT value, mean tumor long-axis diameter, and mean tumor short-axis diameter (r = -0.559, 0.679, -0.430, -0.585, -0.425, and -0.385, respectively, P < 0.05 for all). BMI was positively correlated with the degree of periintestinal invasion, lymph node CT value, and mean tumor short-axis diameter (r = 0.303, 0.431, and 0.437, P < 0.05 for all), as shown in Table 5 and Figure 5.

Figure 5
Figure 5 Scatter plot of correlation between postoperative survival time and abdominal computed tomography signs in patients with colorectal cancer. A: Degree of periintestinal infiltration; B: Tumor size; C: Lymph node computed tomography value; D: Mean tumor long-axis diameter; E: Mean tumor short-axis diameter; F: Body mass index. BMI: Body mass index; CT: Computed tomography.
Table 5 Correlation between postoperative survival time and abdominal computed tomography signs in patients with colorectal cancer.
Independent variable

Survival time
BMI
Degree of periintestinal infiltration
Tumor size
Lymph nodes CT value
Mean tumor long-axis diameter
Mean tumor short-axis diameter
Survival timer value--0.559-0.679-0.430-0.585-0.425-0.385
P value-< 0.001< 0.001< 0.001< 0.001< 0.001< 0.001
BMIr value--0.3030.2540.4310.2110.437
P value--0.0040.017< 0.0010.049< 0.001
Degree of periintestinal infiltrationr value---0.1990.2460.3320.264
P value---0.0630.0210.0020.013
Tumor sizer value----0.3520.3030.276
P value----0.0010.0040.009
Lymph node CT valuer value-----0.3900.420
P value-----< 0.001< 0.001
Mean tumor long-axis diameterr value------0.587
P value------< 0.001
Mean tumor short-axis diameterr value-------
P value-------
DISCUSSION

The high mortality rate of CRC in China is primarily attributed to the local recurrence or metastasis of CRC, and surgery cannot prolong patient survival. Patients with CRC of different stages exhibit different abdominal CT signs and, therefore, require different treatment plans. Clarifying the relationship between abdominal CT signs associated with CRC and patient prognoses is crucial for the early detection of CRC and the improvement of the quality of life of patients[9].

The three-year mortality rate of the 88 patients with CRC was 26.14%, which is lower than the 36% (95% confidence interval: 0.99-0.70) reported by Maajani et al[10]; the difference may be related to the different regions where the patients lived in. A higher proportion of dead patients with CRC had a BMI > 24 kg/m2, pathological stage IV, highly differentiated tumor, severe periintestinal infiltration, tumor size ≥ 4 cm, lymph node CT value ≥ 30 HU, mean tumor long-axis diameter ≥ 0.6 cm, and mean short-axis diameter ≥ 0.45 cm. Additional multivariate Cox regression analysis showed that BMI, degree of intestinal infiltration, tumor size, and lymph node CT value were independent factors influencing the likelihood of postoperative death in patients with CRC. Recent studies have found that obesity affects not only the progression of tumors but also the long-term prognosis of patients[11]. International studies have shown that, compared to CRC patients with a normal BMI, CRC patients with a higher BMI have a higher risk of death, recurrence, and a poorer prognosis[12]. Moreover, obesity is associated with hyperinsulinemia and insulin resistance. High insulin levels can increase the biological activity of insulin-like growth factors and stimulate the proliferation and metastasis of tumor cells. In addition, insulin induces angiogenesis and enhances tumor aggressiveness. Obesity can also promote cancer progression through chronic inflammatory pathways. Several studies have reported that obesity is often accompanied by immunosuppression, and relevant inflammatory factors can exacerbate the systemic inflammatory response (increasing the risk of disease) and further promote a pro-inflammatory and oxidative environment in the body, leading to tumor recurrence or lesion reformation after CRC surgery[13,14]. Doleman et al[15] conducted a systematic review and meta-analysis of observational studies to examine the relationship between BMI and CRC outcomes. The authors found that obese patients had an increased risk of all-cause death [relative risk (RR) = 1.14] and cancer-specific mortality (RR = 1.14). Compared with patients with normal weights, obese patients with CRC had a higher risk of all-cause and cancer-specific deaths.

Invasion and metastasis are important features of malignant tumors and are key factors affecting tumor prognosis. CRC can infiltrate and grow along all layers of the intestinal wall and narrow the intestinal cavity, manifesting phenomena such as tubular intestinal wall stiffness, thickening, poor intestinal expansion, mucosal surface hyperemia and edema, and superficial ulcers[16]. Huang et al[17] showed that tumor-associated macrophage (M2-TAM) infiltration driven by the SPON2 gene significantly contributes to the growth and metastasis of CRC. Therefore, the higher the degree of periintestinal infiltration, the wider the scope of CRC infiltration, the more likely early metastasis will occur, the worse the prognosis, and the higher the risk of death[18]. Furthermore, multiple studies have confirmed that polyp size is one of the most important criteria for assessing benign and malignant lesions, and more than 56% of patients with polyp sizes larger than 2.0 cm are likely to have malignant lesions[19]. Additionally, tumor overload may promote the spread and metastasis of cancer cells[20]. Tumor size is one of the indices used to ascertain the stage of the tumor and can assist in establishing a prognosis. We discovered that tumor size was an independent factor affecting CRC prognoses, which is consistent with the results of previous studies. Lymph nodes, a part of the lymphatic system, filter and remove waste, bacteria, and viruses from the body. CT value is a measure of the density of tissues or organs. A lower CT value for lymph nodes indicates that the lymph node tissues are primarily water sample dense. Moreover, it implies that more cystic components in the lesions are present, and the possibility of benign lesions is higher. In contrast, a high lymph node CT value and dense lymph nodes may be caused by cancer cell metastasis or the infiltration of a malignancy into local tissues[21]. Hence, a high lymph node CT value may predict the progression of CRC, suggesting a poor prognosis and an increased risk of death.

We analyzed in-depth the relationship between risk factors (primarily abdominal CT signs) and CRC prognosis. We found that in CRC patients with a high degree of periintestinal infiltration, tumor size ≥ 4 cm, lymph node CT value ≥ 30 HU, and BMI > 24 kg/m2, the survival rate was significantly lower. In particular, BMI was positively correlated with the degree of periintestinal infiltration, CT value of lymph nodes, and mean short diameter. This further elucidates the relationship between CT signs and surgical prognosis and physical indicators of CRC patients. A high BMI is a predictor related to increased body fat. Suzuki et al[22] showed that BMI was positively correlated with CRC risk. Sensitivity analysis showed that for every unit increase in genetically predicted BMI, the odds ratio for CRC increased. The higher the BMI, the further the development of CRC and the shorter the survival time of patients. The degree of periintestinal invasion, tumor size, CT value of lymph nodes, mean long diameter, mean short diameter, and other CT signs are risk factors leading to high pathological grade in patients with CRC[23]. Zhang et al[24] showed that tumor size is significantly related to the prognosis of CRC. The high degree of periintestinal invasion, tumor size, CT value of lymph nodes, mean long diameter, and mean short diameter predicted the high malignant degree of CRC tumor and reduced the survival time of patients. Bähr et al[25] suggest that obesity promotes the progression and metastasis of cancer, which may be related to the increased expression of MACC1 antibody, which is related to CRC metastasis caused by obesity; however, more studies are required to confirm this conclusion. Our study also showed that high BMI would aggravate CT signs in CRC patients, which were manifested as an increased degree of periintestinal invasion, CT value of lymph nodes, and mean short diameter, which is consistent with previous studies. Therefore, we suggest that in clinical practice, the postoperative prognosis of patients with CRC can be evaluated according to the degree of periintestinal infiltration, tumor size, lymph node CT value, and BMI.

CONCLUSION

This study discovered that abdominal CT examination of patients with CRC can fully reveal the internal state of the tumor. It can also reveal the relationship between the tumor and adjacent tissues and determine the degree of periintestinal infiltration, tumor size, lymph node CT value, and other signs, which are crucial for evaluating the prognosis of patients with CRC. Therefore, understanding the abdominal CT signs of patients with CRC can enable relatively accurate prognosis prediction for the appropriate surgical treatment of CRC and provide a reliable basis for determining clinical treatment plans. However, this study had certain limitations. Specifically, the sample size was relatively small, and the study was conducted in a single center. Thus, the accuracy of the relationship between abdominal CT signs and the postoperative prognosis of patients with CRC should be confirmed by considering a large number of studies with larger sample sizes.

Footnotes

Provenance and peer review: Unsolicited article; Externally peer reviewed.

Peer-review model: Single blind

Specialty type: Gastroenterology and hepatology

Country of origin: China

Peer-review report’s classification

Scientific Quality: Grade C

Novelty: Grade B

Creativity or Innovation: Grade B

Scientific Significance: Grade B

P-Reviewer: Marco C, Netherlands S-Editor: Wang JJ L-Editor: Wang TQ P-Editor: Cai YX

References
1.  Tiffon C. The Impact of Nutrition and Environmental Epigenetics on Human Health and Disease. Int J Mol Sci. 2018;19.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 195]  [Cited by in F6Publishing: 206]  [Article Influence: 34.3]  [Reference Citation Analysis (0)]
2.  Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144:646-674.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 39812]  [Cited by in F6Publishing: 44124]  [Article Influence: 3394.2]  [Reference Citation Analysis (4)]
3.  Baidoun F, Elshiwy K, Elkeraie Y, Merjaneh Z, Khoudari G, Sarmini MT, Gad M, Al-Husseini M, Saad A. Colorectal Cancer Epidemiology: Recent Trends and Impact on Outcomes. Curr Drug Targets. 2021;22:998-1009.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 26]  [Cited by in F6Publishing: 93]  [Article Influence: 31.0]  [Reference Citation Analysis (0)]
4.  Watson DK, McWilliams-Smith MJ, Kozak C, Reeves R, Gearhart J, Nunn MF, Nash W, Fowle JR 3rd, Duesberg P, Papas TS. Conserved chromosomal positions of dual domains of the ets protooncogene in cats, mice, and humans. Proc Natl Acad Sci U S A. 1986;83:1792-1796.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 68]  [Cited by in F6Publishing: 91]  [Article Influence: 2.4]  [Reference Citation Analysis (0)]
5.  Lee JW, Baek MJ, Ahn TS, Lee SM. Fluorine-18-fluorodeoxyglucose uptake of bone marrow on PET/CT can predict prognosis in patients with colorectal cancer after curative surgical resection. Eur J Gastroenterol Hepatol. 2018;30:187-194.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 16]  [Cited by in F6Publishing: 17]  [Article Influence: 2.8]  [Reference Citation Analysis (0)]
6.  Veit-Haibach P, Kuehle CA, Beyer T, Stergar H, Kuehl H, Schmidt J, Börsch G, Dahmen G, Barkhausen J, Bockisch A, Antoch G. Diagnostic accuracy of colorectal cancer staging with whole-body PET/CT colonography. JAMA. 2006;296:2590-2600.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 86]  [Cited by in F6Publishing: 76]  [Article Influence: 4.2]  [Reference Citation Analysis (0)]
7.  Shida D, Inoue M, Tanabe T, Moritani K, Tsukamoto S, Yamauchi S, Sugihara K, Kanemitsu Y. Prognostic impact of primary tumor location in Stage III colorectal cancer-right-sided colon versus left-sided colon versus rectum: a nationwide multicenter retrospective study. J Gastroenterol. 2020;55:958-968.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 24]  [Cited by in F6Publishing: 34]  [Article Influence: 8.5]  [Reference Citation Analysis (0)]
8.  Nieto Y, Nawaz F, Jones RB, Shpall EJ, Nawaz S. Prognostic significance of overexpression and phosphorylation of epidermal growth factor receptor (EGFR) and the presence of truncated EGFRvIII in locoregionally advanced breast cancer. J Clin Oncol. 2007;25:4405-4413.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 68]  [Cited by in F6Publishing: 70]  [Article Influence: 4.1]  [Reference Citation Analysis (0)]
9.  Lv L, Xin B, Hao Y, Yang Z, Xu J, Wang L, Wang X, Song S, Guo X. Radiomic analysis for predicting prognosis of colorectal cancer from preoperative (18)F-FDG PET/CT. J Transl Med. 2022;20:66.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 2]  [Cited by in F6Publishing: 20]  [Article Influence: 10.0]  [Reference Citation Analysis (0)]
10.  Maajani K, Khodadost M, Fattahi A, Shahrestanaki E, Pirouzi A, Khalili F, Fattahi H. Survival Rate of Colorectal Cancer in Iran: A Systematic Review and Meta-Analysis. Asian Pac J Cancer Prev. 2019;20:13-21.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 20]  [Cited by in F6Publishing: 17]  [Article Influence: 3.4]  [Reference Citation Analysis (0)]
11.  Petrelli F, Cortellini A, Indini A, Tomasello G, Ghidini M, Nigro O, Salati M, Dottorini L, Iaculli A, Varricchio A, Rampulla V, Barni S, Cabiddu M, Bossi A, Ghidini A, Zaniboni A. Association of Obesity With Survival Outcomes in Patients With Cancer: A Systematic Review and Meta-analysis. JAMA Netw Open. 2021;4:e213520.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 226]  [Cited by in F6Publishing: 197]  [Article Influence: 65.7]  [Reference Citation Analysis (0)]
12.  Arnold M, Charvat H, Freisling H, Noh H, Adami HO, Soerjomataram I, Weiderpass E. Adult Overweight and Survival from Breast and Colorectal Cancer in Swedish Women. Cancer Epidemiol Biomarkers Prev. 2019;28:1518-1524.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 10]  [Cited by in F6Publishing: 9]  [Article Influence: 1.8]  [Reference Citation Analysis (0)]
13.  Kulkarni A, Bowers LW. The role of immune dysfunction in obesity-associated cancer risk, progression, and metastasis. Cell Mol Life Sci. 2021;78:3423-3442.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 18]  [Cited by in F6Publishing: 17]  [Article Influence: 5.7]  [Reference Citation Analysis (0)]
14.  Sanchez-Pino MD, Gilmore LA, Ochoa AC, Brown JC. Obesity-Associated Myeloid Immunosuppressive Cells, Key Players in Cancer Risk and Response to Immunotherapy. Obesity (Silver Spring). 2021;29:944-953.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 9]  [Cited by in F6Publishing: 3]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
15.  Doleman B, Mills KT, Lim S, Zelhart MD, Gagliardi G. Body mass index and colorectal cancer prognosis: a systematic review and meta-analysis. Tech Coloproctol. 2016;20:517-535.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 70]  [Cited by in F6Publishing: 87]  [Article Influence: 10.9]  [Reference Citation Analysis (0)]
16.  Wang S, Qu Y, Xia P, Chen Y, Zhu X, Zhang J, Wang G, Tian Y, Ying J, Fan Z. Transdifferentiation of tumor infiltrating innate lymphoid cells during progression of colorectal cancer. Cell Res. 2020;30:610-622.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 90]  [Cited by in F6Publishing: 92]  [Article Influence: 23.0]  [Reference Citation Analysis (0)]
17.  Huang C, Ou R, Chen X, Zhang Y, Li J, Liang Y, Zhu X, Liu L, Li M, Lin D, Qiu J, Liu G, Zhang L, Wu Y, Tang H, Liu Y, Liang L, Ding Y, Liao W. Tumor cell-derived SPON2 promotes M2-polarized tumor-associated macrophage infiltration and cancer progression by activating PYK2 in CRC. J Exp Clin Cancer Res. 2021;40:304.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 8]  [Cited by in F6Publishing: 38]  [Article Influence: 12.7]  [Reference Citation Analysis (0)]
18.  Yang Z, Liu Z. The efficacy of (18)F-FDG PET/CT-based diagnostic model in the diagnosis of colorectal cancer regional lymph node metastasis. Saudi J Biol Sci. 2020;27:805-811.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 6]  [Cited by in F6Publishing: 5]  [Article Influence: 1.0]  [Reference Citation Analysis (0)]
19.  Horning AM, Wang Y, Lin CK, Louie AD, Jadhav RR, Hung CN, Wang CM, Lin CL, Kirma NB, Liss MA, Kumar AP, Sun L, Liu Z, Chao WT, Wang Q, Jin VX, Chen CL, Huang TH. Single-Cell RNA-seq Reveals a Subpopulation of Prostate Cancer Cells with Enhanced Cell-Cycle-Related Transcription and Attenuated Androgen Response. Cancer Res. 2018;78:853-864.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 61]  [Cited by in F6Publishing: 70]  [Article Influence: 10.0]  [Reference Citation Analysis (0)]
20.  Greenlee JD, King MR. A syngeneic MC38 orthotopic mouse model of colorectal cancer metastasis. Biol Methods Protoc. 2022;7:bpac024.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 11]  [Reference Citation Analysis (0)]
21.  Cheng Y, Yu Q, Meng W, Jiang W. Clinico-Radiologic Nomogram Using Multiphase CT to Predict Lymph Node Metastasis in Colon Cancer. Mol Imaging Biol. 2022;24:798-806.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 2]  [Reference Citation Analysis (0)]
22.  Suzuki S, Goto A, Nakatochi M, Narita A, Yamaji T, Sawada N, Katagiri R, Iwagami M, Hanyuda A, Hachiya T, Sutoh Y, Oze I, Koyanagi YN, Kasugai Y, Taniyama Y, Ito H, Ikezaki H, Nishida Y, Tamura T, Mikami H, Takezaki T, Suzuki S, Ozaki E, Kuriki K, Takashima N, Arisawa K, Takeuchi K, Tanno K, Shimizu A, Tamiya G, Hozawa A, Kinoshita K, Wakai K, Sasaki M, Yamamoto M, Matsuo K, Tsugane S, Iwasaki M. Body mass index and colorectal cancer risk: A Mendelian randomization study. Cancer Sci. 2021;112:1579-1588.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in Crossref: 17]  [Cited by in F6Publishing: 21]  [Article Influence: 7.0]  [Reference Citation Analysis (0)]
23.  Bülbül HM, Burakgazi G, Kesimal U. Preoperative assessment of grade, T stage, and lymph node involvement: machine learning-based CT texture analysis in colon cancer. Jpn J Radiol. 2024;42:300-307.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]
24.  Zhang Q, Li B, Zhang S, Huang Q, Zhang M, Liu G. Prognostic impact of tumor size on patients with metastatic colorectal cancer: a large SEER-based retrospective cohort study. Updates Surg. 2023;75:1135-1147.  [PubMed]  [DOI]  [Cited in This Article: ]  [Cited by in F6Publishing: 4]  [Reference Citation Analysis (0)]
25.  Bähr I, Jaeschke L, Nimptsch K, Janke J, Herrmann P, Kobelt D, Kielstein H, Pischon T, Stein U. Obesity, colorectal cancer and MACC1 expression: A possible novel molecular association. Int J Oncol. 2022;60.  [PubMed]  [DOI]  [Cited in This Article: ]  [Reference Citation Analysis (0)]