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Prognostic value of diffusion-weighted imaging to cytoreductive surgery with or without hyperthermic intraperitoneal chemotherapy for patients with gastric cancer and peritoneal metastases

BMC Cancer volume 25, Article number: 616 (2025) Cite this article

Abstract

Background

To investigate the prognostic value of the apparent diffusion coefficient (ADC) calculated from diffusion-weighted imaging (DWI) to cytoreductive surgery (CRS), with or without hyperthermic intraperitoneal chemotherapy (HIPEC), for gastric cancer (GC) patients with peritoneal metastasis (PM).

Methods

Between May 2016 and December 2020, 95 newly diagnosed GC patients with PM who underwent CRS combined with HIPEC (CRS + HIPEC group, n = 61) and CRS alone (CRS group, n = 34) were retrospectively included. All patients underwent abdominal 3.0 T MRI scan, including DWI, and the mean ADC (ADCmean), minimum ADC (ADCmin), and maximum ADC (ADCmax) values of the whole-volume tumor were measured. The prognostic value of the ADC parameters and clinical and histopathological characteristics were investigated by univariate and multivariate Cox analyses.

Results

The median overall survival (OS) periods of the CRS + HIPEC and CRS groups were 18 and 9 months, respectively ([hazard ratio (HR) = 0.44 [95% CI: 0.27–0.71], P<0.001). The ADCmean and ADCmin values were positively correlated with OS in all patients (Spearman’s rho [R] = 0.361 and 0.470), as well as in the CRS + HIPEC (R = 0.369 and 0.417) and CRS (R = 0.192 and 0.409) groups. The multivariate Cox analysis demonstrated that the ADCmean ≤ 1.39 × 10− 3 mm2/s and ADCmin ≤ 0.77 × 10− 3 mm2/s were significantly associated with a negative prognosis in the total population (HR = 1.68 [95% CI: 1.02–2.75] and 2.48 [95% CI: 1.51–4.08], P all < 0.05) and the CRS + HIPEC group (HR = 2.22 [95% CI: 1.19–4.14] and 2.37 [95% CI: 1.26–4.37], P all < 0.05), along with pathologic T and N stages. Only the ADCmin ≤ 0.77 × 10− 3 mm2/s was identified as an independent prognostic factor in the CRS group (HR = 3.49 [95% CI: 1.19–10.20], P = 0.022).

Conclusions

The minimum ADC was identified as a strong independent prognostic factor for GC patients with PM who underwent CRS, with or without HIPEC.

Peer Review reports

Background

Gastric cancer (GC) is the fifth most common malignancy and the fourth leading cause of cancer-related deaths worldwide [1]. The peritoneum is the most common site of metastasis in GC; peritoneal metastasis (PM) has been reported in 20–30% of newly diagnosed patients. Although super-extended (D2plus) D2plus lymphadenectomy after chemotherapy for locally advanced or oligometastatic gastric cancer is feasible and associated with low morbidity/mortality rates [2]. Most of the advanced cases of GC will develop PM within two years of radical surgery for the cancer [3]. The prognosis for GC with PM remains highly poor, even though a standard systemic chemotherapy protocol for the condition has been developed. GC patients with PM have a median overall survival (OS) period of only 8–13 months [4,5,6].

Complete cytoreductive surgery (CRS), with or without hyperthermic intraperitoneal chemotherapy (HIPEC), is currently the only therapeutic strategy available for improving prognosis in most cases of PM [7,8,9]. CRS combined with HIPEC (CRS + HIPEC) confers major benefits compared with those achieved with CRS alone in colon and ovarian cancers [7, 9]. However, for GC, the use of CRS + HIPEC remains controversial. Previous multi-center clinical studies have demonstrated that CRS + HIPEC could improve the OS and recurrence-free survival (RFS) compared to that achieved with CRS alone [6, 10]. However, another clinical trial demonstrated that CRS + HIPEC could not improve prognosis [11]. Because of the high tumor heterogeneity and individual differences among patients with GC and PM, the prognostic value of the routine TNM staging system for CRS, with or without HIPEC, is limited and debatable [6, 11, 12]. Therefore, it becomes imperative to explore noninvasive and effective prognostic markers to predict treatment outcomes.

Computed tomography (CT) is the most common noninvasive method for the detection and characterization of GC. Some recent technological developments related to magnetic resonance imaging (MRI), including fast imaging techniques, respiratory motion compensation techniques, use of anti-peristaltic agents, and the introduction of functional MRI, have made MRI a more desirable imaging technique for GC [13]. Diffusion-weighted imaging (DWI)—an advanced MRI technique—allows noninvasive assessment of the biologic features of tumors and is now incorporated into routine clinical practice. Additional DWI could improve the diagnostic sensitivity and detection accuracy for the PM compared to that achieved with conventional MRI alone [14]. In particular, apparent diffusion coefficient (ADC) parameters measured using DWI can be employed for noninvasive and quantitative assessment of tumor cellularity and the biologic structure. These parameters can be used for the diagnosis and prognostic prediction in GC, as well as for evaluating the effects of adjuvant chemotherapy [13, 15]. The mean ADC (ADCmean) is significantly correlated with TNM stages and invasiveness in GC [16,17,18]. In addition, ADCmean can be used to identify the response to neoadjuvant chemotherapy for locally advanced GC [19,20,21] and predict the RFS and OS for resectable GC after radical surger [22,23,24]. As reported in a recent study, apart from the ADCmean, the minimum ADC (ADCmin) is also significantly correlated with GC histological types and differentiation [25]. In addition, the ADCmin and the maximum ADC (ADCmax) are valuable parameters for assessing tumor aggressiveness and prognosis in breast cancer, hepatocellular carcinoma, and nasopharyngeal carcinoma [26,27,28].

On the basis of these findings, we hypothesized that apart from the ADCmean, the ADCmin and ADCmax values can also be employed for predicting the treatment outcomes for patients with GC and PM. This study explores the prognostic value of multiparameter ADC values for patients with GC and PM treated with CRS alone or with CRS + HIPEC.

Materials and methods

Patient selection

This retrospective study was approved by the Institutional Review Board of Affiliated Cancer Hospital & Institute of Guangzhou Medical University. The requirement for informed consent was waived off as it is a retrospective study. Between May 2016 and December 2020, a total of 132 newly diagnosed GC patients with PM, as confirmed by surgical pathology, were identified based on the following inclusion criteria: (a) GC patients with PM who underwent CRS, with or without HIPEC; (b) patients who underwent abdomen 3.0 T MRI, including DWI, before CRS; and (c) patients without distant metastasis at other sites, except for the peritoneum. The exclusion criteria were as follows: (a) patients who had undergone systemic chemotherapy before CRS (n = 28); (b) poor quality of DWI (n = 4); and (c) a follow-up period of < 1 month (n = 5). All cases were evaluated by a multidisciplinary oncology team (MDT), consisting of oncologists, surgeons, radiologists, and nutritionists, to ensure comprehensive treatment planning [29]. The final patient population comprised 95 patients—34 in the CRS group and 61 in the CRS + HIPEC group (Fig. 1).

Fig. 1
figure 1

Flow chart of the patient recruitment pathway

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Acquisition of MR images

All patients underwent epigastric MRI examinations using a 3.0T (Discovery 750, GE Healthcare, Milwaukee, Wisconsin, USA) scanner with a phased-array 16-channel sensitivity encoding abdominal coil prior to HIPEC. Before performing the MR examination, the patients fasted for at least 8 h and drank 500–700 mL of warm water immediately before scanning to distend the gastric lumen. This step was coordinated with respiratory training to ensure normal scan implementation and reduce image motion artifacts. Next, 20 mg of scopolamine–butylbromide was administered through intramuscular injection to control gastric motility after patient positioning. The scanning field of view covered the entire stomach region from the diaphragmatic dome to the level of the renal hilum. Following the method described in previous studies [17, 22], the axial DWI (b = 0 and 600 s/mm2) was carried out by using a respiratory-triggered single-shot spin-echo echo-planar sequence. The ADC map was automatically generated on a voxel-by-voxel basis from the two b-values. Aside from DWI, an axial T2-weighted imaging, with and without fat suppression, and a dynamic enhanced T1-weighted imaging with fat suppression were also performed. For dynamic enhanced T1-weighted imaging, 0.1 mmol/kg of body weight of Gd-DTPA (Magnevist; Schering, Berlin, Germany) was intravenously administered with an automatic injector at a rate of 2.0 mL/s. The detailed MRI parameters are listed in Table 1.

Table 1 MR imaging parameters
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Multiparameter ADC measurements

The ADC measurements were independently performed on a dedicated post-processing workstation (AW VolumeShare 4.7; GE Healthcare, Milwaukee, Wisconsin, USA) by two radiologists (Observer 1: JS, with 8 years of experience in MRI diagnosis; Observer 2: JXY, with 10 years of experience in MRI diagnosis). Before ADC measurements, the tumor location was evaluated by consensus between the two observers to make sure that the regions of interest (ROIs) were positioned on the same lesion. The observers were blinded to pathological findings as well as to the treatment and prognostic results of the patients. Using the method detailed elsewhere [22, 30], the whole-volume ADC values of the tumor were measured by placing ROIs slice by slice on ADC maps. ROIs covered the edge of the lesion and were drawn along the inner margin of the gastric walls to avoid the inclusion of water in the ROIs. The necrotic components (identified by the remarkable hyperintensity on T2W images and hypointensity on DW images) of the tumor were carefully eliminated. The ADC measurement diagram is shown in Fig. 2. The mean values of the ROI area (sum of all sections), as determined by the two observers, were 36.71 ± 19.78 and 36.12 ± 20.11cm2. Multiparameter ADC values for each section were recorded, including the mean ADC (ADCmean), minimum ADC (ADCmin), and maximum ADC (ADCmax). Next, the whole-volume ADC values were calculated by averaging the measured ADC values for all sections. The ADC values measured by the two observers were averaged, and the mean values were used for statistical analysis.

Fig. 2
figure 2

Measurement of apparent diffusion coefficients (ADCs). The whole-volume ADC values of the tumor were measured by placing regions of interest (ROIs) slice by slice on ADC maps (the illustration only displayed three consistent slices). ROIs covered the edge of the lesion and were drawn along the inner margin of the gastric walls to avoid the inclusion of water in the ROIs. The necrotic components of the tumor were carefully eliminated. Multiparameter ADC values for each section were recorded, including the mean ADC (ADCmean), minimum ADC (ADCmin), and maximum ADC (ADCmax). Whole-volume ADC values were calculated by averaging the measured ADC values for all sections

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CRS and HIPEC procedures

All the 95 patients received complete CRS, which is the surgical removal of visible tumors in the abdominal cavity as completely as possible to reduce tumor burden, including the primary tumor with lymphadenectomy, greater omentectomy, and resection of all peritoneal deposits by combining peritonectomy procedures and resections of any involved organ. The CRS completeness was evaluated using the completeness of cytoreduction (CC) score [31], as follows: (1) CC-0: no residual peritoneal disease after CRS; (2) CC-1: <0.25 cm of residual disease; (3) CC-2: between 0.25 and 2.5 cm of residual disease; and (4) CC-3: >2.5 cm of residual tumor or the presence of a sheet of unresectable tumor nodules. Only the CC scores of 0 and 1 were identified as CRS completeness.

In the 61 patients who underwent the CRS + HIPEC treatment protocol by using the closed treatment mode, four perfusion tubes (two for inflow and two for outflow) were placed under laparoscopic or direct open visual guidance, allowing continuous peritoneal lavage perfusion in a closed abdominal state. As described in previous study [32], the heated perfusate was circulated at a flow rate of 400 − 600 mL/min and a perfusion volume of 2 L/m2 for 60–90 min was delivered using the BRTRG-I hyperthermic perfusion intraperitoneal treatment system (Bright Medical Tech., Guangzhou, China). The perfusion temperature was 43 ± 0.1 °C. The following chemotherapy drug dosages were employed: paclitaxel (75–100 mg/m2) or platinum (oxaliplatin: 100–130 mg/m2 or cisplatin: 50–75 mg/m2). HIPEC was implemented on days 1, 3, and 5, 3–5 times as needed, with a median frequency of 3 (range: 2–5).

Follow-up

The endpoint of this study was the OS period from CRS to death from any cause or the last follow-up of the surviving patient. The OS status was determined from the visit to the outpatient department or via telephone calls to patients who could not go for regular hospital visits. The last patient was included in December 2020. The cut-off time for the final follow-up was November 2023, ensuring a potential minimal follow-up period of 36 months. The 3-year OS rate was determined for both the CRS alone and CRS + HIPEC groups.

Statistical analyses

All statistical analyses of the data were implemented by using R software (version 4.0.2; https://www.r-project.org). P < 0.05 was identified as statistically significant. Continuous quantitative data were presented as the mean ± standard deviation (SD) or median (range). The independent t-test or Mann–Whitney U-test was applied to compare differences among the data that obeyed or did not obey normal distribution, respectively. Categorical variables and the 3-year OS rates were expressed as numbers (%). Pearson’s χ2 was performed to analyze the differences. The interobserver reproducibility of ADC measurements between the two observers was assessed based on intraclass correlation coefficients (ICC). An ICC of > 0.75 indicated good reproducibility [33]. Univariate Cox regression analysis was used to evaluate the potential association of clinicopathological features and multiparameter ADC values with death. A multivariate Cox regression analysis was performed to determine the independent relative risk for death. Spearman’s correlation coefficient (R) was applied to assess the correlation of multiparameter ADC values with the OS period. The Kaplan–Meier survival curve was employed to determine the relationship between multiparameter ADC values and OS by using the log-rank test.

Results

Patient characteristics

Among the 95 GC patients with PM, 61 patients (64.21%) were grouped into the CRS + HIPEC group and 34 patients (35.79%) were assigned to the CRS group, based on the therapeutic methods used. The following frequencies of the baseline characteristics were employed: age, gender, tumor site, pathological TN stage, histologic type, and systemic chemotherapy (Table 2). No statistical significance was observed among the baseline characteristics of the CRS + HIPEC and CRS groups. The median follow-up period was 22 months (range: 2–65 months) for the CRS + HIPEC group (47 of 61 events [77.05%]) and 12 months (range: 2–44 months) for the CRS group (30 of 34 events [88.24%]), while it was 16 months (range: 2–65 months) for all patients. As shown in Fig. 3, the OS of patients treated with CRS + HIPEC was significantly longer than that of those treated with CRS alone (median OS: 18 vs. 9 months, hazard ratio [HR] = 0.44 [95% CI: 0.27–0.71], P < 0.001). The 3-year OS rate of patients treated with CRS + HIPEC was also significantly higher than that of those treated with CRS alone (32.79% vs. 11.76%, P = 0.024). The detailed characteristics are listed in Table 2.

Table 2 Patient characteristics
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Fig. 3
figure 3

Comparison of the overall survival (OS) values of the CRS + HIPEC and CRS groups. The OS period of the CRS + HIPEC group was significantly longer than that of the CRS group (a). Kaplan–Meier analysis indicated that the CRS + HIPEC group had a significantly longer OS than that of the CRS group (HR = 0.44, P < 0.001) (b). CRS, cytoreductive surgery; HIPEC, hyperthermic intraperitoneal chemotherapy

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Interobserver agreement for ADC measurements

The ADCmean and ADCmin measurements demonstrated excellent interobserver reproducibility, with the ICC values of 0.881 (95% confidence interval [CI]: 0.823, 0.921) and 0.846 (95% CI: 0.773, 0.897), respectively. The interobserver reproducibility of ADCmax was also good (ICC = 0.704, 95% CI: 0.578, 0.797). As shown in Fig. 4a-c, Spearman’s correlation analysis plot presented good agreement for ADC measurements determined by the two observers, with the correlation coefficient rho (R) values of 0.827, 0.84, and 0.674 for ADCmean, ADCmin, and ADCmax, respectively. The average of these ADC values, as displayed in Table 3; Fig. 4d, showed no significant difference between the CRS + HIPEC and CRS groups.

Fig. 4
figure 4

Spearman’s correlation plots presented good measurements agreement for the ADCmean(a), ADCmin(b), and ADCmax(c) between two observers, with the correlation coefficient rho (R) values of 0.827, 0.84, and 0.674, respectively. The ADCmean, ADCmin, and ADCmax values of the CRS + HIPEC and CRS groups showed no significant difference (d). ADC, apparent diffusion coefficient; ADCmean, mean ADC; ADCmin, minimum ADC; ADCmax, maximum ADC; CRS, cytoreductive surgery; HIPEC, hyperthermic intraperitoneal chemotherapy

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Table 3 Difference comparison of ADC parameters between all patients, CRS + HIPEC group, and CRS group
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The median ADC values for all patients were used as the cutoff for risk grouping. As shown in Table 4, univariate Cox analysis indicated that ADCmean ≤ 1.39 × 10− 3 mm2/s and ADCmin ≤ 0.77 × 10− 3 mm2/s were associated with a negative prognosis in all patients, as well as in the CRS + HIPEC and CRS groups; however, no such prognostic value was observed for ADCmax. Pathologic TN stages and differentiation were identified as strong prognostic factors for all patients, while pathologic TN and T stages and differentiation were found to be strong prognostic factors in the CRS + HIPEC and CRS groups, respectively. The multivariate analysis demonstrated that ADCmean ≤ 1.39 × 10− 3 mm2/s and ADCmin ≤ 0.77 × 10− 3 mm2/s, along with pathologic T and N stages, were independently associated with death risk among all patients (HR = 1.68 [95% CI: 1.02–2.75] and 2.48 [95% CI: 1.51–4.08], P all < 0.05) as well as in the CRS + HIPEC group (HR = 2.22 [95% CI: 1.19–4.14]) and 2.37 [95% CI: 1.26–4.37], P all < 0.05) (Table 5). Only ADCmin ≤ 0.77 × 10− 3 mm2/s was identified as an independent death risk factor in the CRS group (HR = 3.49 [95% CI: 1.19–10.20], P = 0.022)

Table 4 Univariate Cox analysis and relative risk for death
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Table 5 Multivariate Cox analysis and relative risk for death
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Association of ADCmean and ADCmin with OS

The ADCmean was found to be positively related to the OS period among all patients (R = 0.361, P < 0.01) (Fig. 5a), as well as with the CRS + HIPEC group (R = 0.369, P = 0.003) (Fig. 5b). However, no significant relation was observed between the ADCmean and the OS period for the CRS group (R = 0.192, P = 0.276) (Fig. 5c). Kaplan–Meier analysis indicated that patients with ADCmean ≤ 1.39 × 10− 3 mm2/s had a significantly shorter OS period than that in patients with ADCmean > 1.39 × 10− 3 mm2/s in all patients (median OS: 11 vs. 22 months, HR = 2.11 [95% CI: 1.34–3.35], P = 0.001) (Fig. 5d), as well as in the CRS + HIPEC group (median OS: 14 vs. 40 months, HR = 2.18 [95% CI: 1.20–3.93], P = 0.010) (Fig. 5e) and the CRS group (median OS: 8 vs. 15 months, HR = 2.48 [95% CI: 1.16–5.32], P = 0.019) (Fig. 5f). The ADCmin was positively correlated to the OS period in all patients (R = 0.470, P < 0.01) (Fig. 6a) and in the CRS + HIPEC (R = 0.417, P < 0.01) (Fig. 6b) and CRS groups (R = 0.409, P = 0.016) (Fig. 6c). Kaplan–Meier analysis indicated that ADCmin ≤ 0.77 × 10− 3 mm2/s was associated with a significantly shorter OS period than that achieved when ADCmin > 0.77 × 10− 3 mm2/s in all patients (median OS: 10 vs. 31 months, HR = 2.40 [95% CI: 1.51–3.81], P < 0.01) (Fig. 6d), the CRS + HIPEC group (median OS: 14 vs. 40 months, HR = 1.83 [95% CI: 1.03–3.33], P = 0.039) (Fig. 6e), and the CRS group (median OS: 8 vs. 15 months, HR = 4.72 [95% CI: 1.82–12.15], P = 0.001) (Fig. 6f).

Fig. 5
figure 5

Relationship between the ADCmean and OS for patients who underwent CRS, with or without HIPEC. Spearman’s correlation plots showed that the ADCmean was trended to positively associate with the OS period in all patients (a) and in the CRS + HIPEC (b) and CRS groups (c), with the correlation coefficient rho (R) values of 0.361, 0.369, and 0.192, respectively. Kaplan–Meier analysis indicated that patients with ADCmean ≤ 1.39 × 10− 3 mm2/s had significantly shorter OS periods than those with ADCmean > 1.39 × 10− 3 mm2/s in all patients (HR = 2.11, P = 0.001) (d) and in CRS + HIPEC (HR = 2.18, P = 0.010) (e) and CRS groups (HR = 2.48, P = 0.019) (f). ADC, apparent diffusion coefficient; ADCmean, mean ADC; CRS, cytoreductive surgery; HIPEC, hyperthermic intraperitoneal chemotherapy

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Fig. 6
figure 6

Relationship between the ADCmin and OS in patients who received CRS, with or without HIPEC. Spearman’s correlation plots showed that the ADCmin was positively related to the OS period in all patients (a) and in CRS + HIPEC (b) and CRS groups (c), with the correlation coefficient rho (R) values of 0.470, 0.417, and 0.409, respectively. Kaplan–Meier analysis indicated that patients with ADCmin ≤ 0.77 × 10− 3 mm2/s had a significantly shorter OS period than that in those with ADCmean > 0.77 × 10− 3 mm2/s in all patients (HR = 2.40, P < 0.001) (d) and in CRS + HIPEC (HR = 1.83, P = 0.039) (e) and CRS groups (HR = 4.72, P = 0.001) (f). ADC, apparent diffusion coefficient; ADCmean, mean ADC; ADCmin, minimum ADC; CRS, cytoreductive surgery; HIPEC, hyperthermic intraperitoneal chemotherapy; OS, overall survival

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Discussion

This study demonstrated that the OS in patients treated with CRS + HIPEC was significantly longer than in those treated with CRS alone (HR = 0.44, P < 0.001). Additionally, the ADCmean value was markedly positively correlated with the OS period in all patients (R = 0.361, P < 0.01), as well as in the CRS + HIPEC group (R = 0.369, P = 0.003). The ADCmin was significantly positively correlated with the OS period in all patients (R = 0.470, P < 0.01) and in the CRS + HIPEC (R = 0.417, P < 0.01) and CRS groups (R = 0.409, P = 0.016). In particular, the ADCmin was identified as a strong independent prognostic factor. The patients with ADCmin ≤ 0.77 × 10− 3 mm2/s had a significantly shorter OS period than those with ADCmin > 0.77 × 10− 3 mm2/s (all patients: HR = 2.40, P < 0.01; CRS + HIPEC group: HR = 1.83, P = 0.039; CRS group: HR = 4.72, P = 0.001). Therefore, our results suggested that ADC measurements can be employed as a noninvasive and dependable method for predicting prognosis in GC patients with PM who underwent CRS, regardless of whether they underwent HIPEC too.

The survival benefits of the CRS + HIPEC protocol for GC remain controversial because of the incomplete nature of the CRS protocol [12]. A previous retrospective study [11] on 159 patients reported a median OS of only 9.2 months for patients undergoing CRS + HIPEC. Notably, the CRS could be completed in only 56% of patients. The largest multicenter prospective study (CYTO-CHIP) conducted so far [6] identified 277 GC patients with PM who were treated with complete CRS, with or without HIPEC, and illustrated that the CRS + HIPEC protocol significantly improved both the median OS (18.8 months) and the 3-year OS rate (26.21%) compared with those (12.1 months and 10.82%, respectively) achieved with CRS alone. Similarly, the median OS (18 months) and the 3-year OS rate (32.79%) of the CRS + HIPEC group were significantly higher than those of the CRS group (9 months and 11.76%, respectively). Thus, the CRS + HIPEC protocol can be considered a more promising and valuable therapeutic strategy for GC patients with PM than the CRS protocol, even when the latter was complete.

GC demonstrates high tumor heterogeneity. In addition, the OS is extremely variable even in patients with the same TNM staging and undergoing the same therapeutic strategies. Therefore, it is crucial to identify feasible prognostic markers for predicting OS in patients with GC. The ADCmean is considered a reliable indicator for predicting the response to neoadjuvant chemotherapy. It is well known that responses to neoadjuvant therapies are associated with prognosis. Li et al. [21]analyzed the baseline ADCmean by considering tumor regression grade (TRG) as the reference standard and demonstrated that the ADCmean has a negative association with the TRG (r = -0.292) and reported an AUC of 0.673 for predicting the treatment response. Some recent studies have shown that the ADCmean is associated with survival prognosis in several malignancies; low ADCmean values are frequently associated with aggressive tumor behavior and worse prognosis, such as in breast cancer [22], cervical cancer [34], and colorectal cancer [26]. Previous studies [17, 22] showed that ADC can be considered a prognostic biomarker for OS and risk stratification in GC. Giganti et al. [22] demonstrated that an ADCmean ≤ 1.5 × 10− 3 mm2/s is associated with a poorer OS in patients who underwent a radical surgery, both in the surgery-only and surgery combined with postoperative chemotherapy groups. Another study [17] focused on the association of the ADCmean with OS in GC patients after radical operation. Patients with an ADCmean ≤ 1.36 × 10–3 mm2/s demonstrated markedly lower OS than patients with ADC > 1.36 × 10–3 mm2/s. In line with these findings, we observed a significant prognostic value of the ADCmean in GC patients with PM. Patients with ADCmean ≤ 1.39 × 10− 3 mm2/s showed significantly shorter OS than those with ADCmean > 1.39 × 10− 3 mm2/s, both in the total population as well as in the CRS + HIPEC and CRS groups. Thus, regardless of the treatment combination protocol of HIPEC, ADCmean can be employed as a noninvasive and useful marker to predict the OS of GC patients with PM after they have undergone CRS.

ADC is inversely correlated with tissue cellularity [35]. Theoretically, the region showing the ADCmin may reflect the area with the highest cellularity within the tumor, and the region with the ADCmax may be considered the area with the lowest cellularity composed of stroma. Thus, compared with the ADCmean alone, multi-parameter ADCs may provide additional information that may allow a comprehensive evaluation of tumor heterogeneity and strengthen the clinical application value of ADC measurements. In our previous studies [27, 28], we demonstrated that the ADCmin exhibits a superior diagnostic efficiency than ADCmean in the discrimination of malignant and benign cirrhosis nodules [27]. Both the ADCmin and ADCmax are significantly correlated with the programmed death-ligand 1 expression score [28]. Moreover, a previous study [36] demonstrated that the ADCmin and ADCmax values can be used to identify invasive components in ductal breast cancer in situ diagnosed with biopsy. According to Liu et al. [25], the ADCmin value is significantly correlated with histological differentiation and Lauren classification in GC. Owing to the potential values of ADCmin and ADCmax in assessing the tumor aggressiveness and heterogeneity, we assumed that these two values may provide valuable information for predicting the OS of patients with GC in clinical practice.

We investigated the values of ADCmin and ADCmax for predicting OS in GC patients with PM. Although the ADCmax did not show any prognostic value, the ADCmin was found to be markedly associated with the OS period in the total patient population, as well as in the CRS + HIPEC and CRS groups. Patients with ADCmin ≤ 0.77 × 10− 3 mm2/s had a significantly shorter OS than those with ADCmin > 0.77 × 10− 3 mm2/s in the total population, as well as in the CRS + HIPEC and CRS groups. This uncertain prognostic value of ADCmax can partially be explained by the fact that cystic necrosis in the tumor may not be completely excluded when placement ROIs, especially the cystic necrosis, is too small to recognize. Furthermore, the water in the gastral cavity shows marked hyperintensity on ADC maps, which may influence the ADCmax measurements. Our findings were similar to those reported by Kim et al. [37], who demonstrated that the distant metastasis-free survival (DMFS) risk of patients with breast cancer could be accurately classified with the optimal cutoff value of ADCmin≤ 0.71 × 10 − 3 mm2/s; however, no significant relation was observed between ADCmax and DMFS.

Our study has some limitations too, such as the relatively small sample size (n = 95) and the distribution of the patients into two distinct and unequal treatment subgroups (n = 61 vs. n = 34). In addition, as it was a single-center, retrospective study, it became difficult to completely avoid the selection bias because we included only GC patients who had undergone MRI and DWI before CRS. A future multicentered prospective study is needed to verify the results generated. Moreover, the HIPEC frequency was not consistent and ranged from 2 to 5 times, because of the retrospective nature of the study, which may affect the prognosis of patients. Further multicenter and prospective studies are needed for probing the association of HIPEC frequency with survival outcomes. Finally, only three ADC values were calculated and used. A histogram or radiomic analysis should be performed, as it can better reflect tumor heterogeneity.

Conclusion

This study showed that the ADCmin and ADCmax parameters could be used to predict the treatment outcomes for GC patients with PM. Lower ADCmean and ADCmin values before the patients were subjected to CRS were associated with poorer OS in GC patients with PM, regardless of whether HIPEC was used or not. The ADCmin, in particular, was identified as a strong independent prognostic factor for GC patients undergoing not only CRS alone, but also CRS + HIPEC. The study results suggested that the quantitative analysis of the ADCmin can be employed as a prognostic marker for GC with PM and develop personalized treatment and surveillance plans for such patients.

Data availability

The datasets used and/or analyzed during the current study available from the corresponding author upon reasonable request.

Abbreviations

GC:

Gastric cancer

PM:

Peritoneal metastasis

CRS:

Cytoreductive surgery

HIPEC:

Hyperthermic intraperitoneal chemotherapy

OS:

Overall survival

HR:

Hazard ratio

DWI:

Diffusion-weighted imaging

ADC:

Apparent diffusion coefficients

ADCmean :

Mean ADC

ADCmin :

Minimum ADC

ADCmax :

Maximum ADC

ICC:

Interclass correlation coefficients

ROI:

Region of interest

DMFS:

Distant metastasis-free survival

TRG:

Tumor regression grade

References

  1. Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49.

    PubMed  Google Scholar 

  2. Raj N, Andrews BT, Sood R, Saani I, Conroy M. Amyand’s hernia: A radiological solution of a surgical dilemma. Cureus. 2023;15(1):e33983.

    PubMed  PubMed Central  Google Scholar 

  3. Thomassen I, van Gestel YR, van Ramshorst B, Luyer MD, Bosscha K, Nienhuijs SW, et al. Peritoneal carcinomatosis of gastric origin: A population-based study on incidence, survival and risk factors. Int J Cancer. 2014;134(3):622–8.

    CAS  PubMed  Google Scholar 

  4. Bernards N, Creemers GJ, Nieuwenhuijzen GA, Bosscha K, Pruijt JF, Lemmens VE. No improvement in median survival for patients with metastatic gastric cancer despite increased use of chemotherapy. Ann Oncol. 2013;24(12):3056–60.

    CAS  PubMed  Google Scholar 

  5. Muro K, Chung HC, Shankaran V, Geva R, Catenacci D, Gupta S, et al. Pembrolizumab for patients with PD-L1-positive advanced gastric cancer (KEYNOTE-012): A multicentre, open-label, phase 1b trial. Lancet Oncol. 2016;17(6):717–26.

    CAS  PubMed  Google Scholar 

  6. Bonnot PE, Piessen G, Kepenekian V, Decullier E, Pocard M, Meunier B, et al. Cytoreductive surgery with or without hyperthermic intraperitoneal chemotherapy for gastric cancer with peritoneal metastases (CYTO-CHIP study): A propensity score analysis. J Clin Oncol. 2019;37(23):2028–40.

    CAS  PubMed  Google Scholar 

  7. Elias D, Lefevre JH, Chevalier J, Brouquet A, Marchal F, Classe JM, et al. Complete cytoreductive surgery plus intraperitoneal chemohyperthermia with oxaliplatin for peritoneal carcinomatosis of colorectal origin. J Clin Oncol. 2009;27(5):681–5.

    PubMed  Google Scholar 

  8. Yan TD, Deraco M, Baratti D, Kusamura S, Elias D, Glehen O, et al. Cytoreductive surgery and hyperthermic intraperitoneal chemotherapy for malignant peritoneal mesothelioma: Multi-institutional experience. J Clin Oncol. 2009;27(36):6237–42.

    PubMed  Google Scholar 

  9. de Bree E, Michelakis D. An overview and update of hyperthermic intraperitoneal chemotherapy in ovarian cancer. Expert Opin Pharmacother. 2020;21(12):1479–92.

    PubMed  Google Scholar 

  10. Marano L, Marrelli D, Sammartino P, Biacchi D, Graziosi L, Marino E, et al. Cytoreductive surgery and hyperthermic intraperitoneal chemotherapy for gastric cancer with synchronous peritoneal metastases: multicenter study of ‘italian peritoneal surface malignancies oncoteam-S.I.C.O’. Ann Surg Oncol. 2021;28(13):9060–70.

    PubMed  PubMed Central  Google Scholar 

  11. Glehen O, Gilly FN, Arvieux C, Cotte E, Boutitie F, Mansvelt B, et al. Peritoneal carcinomatosis from gastric cancer: A multi-institutional study of 159 patients treated by cytoreductive surgery combined with perioperative intraperitoneal chemotherapy. Ann Surg Oncol. 2010;17(9):2370–7.

    PubMed  Google Scholar 

  12. Coccolini F, Catena F, Glehen O, Yonemura Y, Sugarbaker PH, Piso P, et al. Complete versus incomplete cytoreduction in peritoneal carcinosis from gastric cancer, with consideration to PCI cut-off. Systematic review and meta-analysis. Eur J Surg Oncol. 2015;41(7):911–9.

    CAS  PubMed  Google Scholar 

  13. Borggreve AS, Goense L, Brenkman HJF, Mook S, Meijer GJ, Wessels FJ, et al. Imaging strategies in the management of gastric cancer: current role and future potential of MRI. Br J Radiol. 2019;92(1097):20181044.

    PubMed  PubMed Central  Google Scholar 

  14. Bozkurt M, Doganay S, Kantarci M, Yalcin A, Eren S, Atamanalp SS, et al. Comparison of peritoneal tumor imaging using conventional MR imaging and diffusion-weighted MR imaging with different B values. Eur J Radiol. 2011;80(2):224–8.

    PubMed  Google Scholar 

  15. Giganti F, Tang L, Baba H. Gastric cancer and imaging biomarkers: part 1 - a critical review of DW-MRI and CE-MDCT findings. Eur Radiol. 2019;29(4):1743–53.

    PubMed  Google Scholar 

  16. Liu S, Wang HX, Guan W, Pan L, Zhou ZP, Yu HP, et al. Preoperative apparent diffusion coefficient value of gastric cancer by diffusion-weighted imaging: correlations with postoperative TNM staging. J Magn Reson Imaging. 2015;42(3):837–43.

    PubMed  Google Scholar 

  17. Giganti F, Ambrosi A, Chiari D, Orsenigo E, Esposito A, Mazza E, et al. Apparent diffusion coefficient by diffusion-weighted magnetic resonance imaging as a sole biomarker for staging and prognosis of gastric cancer. Chin J Cancer Res. 2017;29(2):118–26.

    PubMed  PubMed Central  Google Scholar 

  18. Soydan L, Demir AA, Torun M, Cikrikcioglu MA. Use of diffusion-weighted magnetic resonance imaging and apparent diffusion coefficient in gastric cancer staging. Curr Med Imaging. 2020;16(10):1278–89.

    CAS  PubMed  Google Scholar 

  19. De Cobelli F, Giganti F, Orsenigo E, Cellina M, Esposito A, Agostini G, et al. Apparent diffusion coefficient modifications in assessing gastro-oesophageal cancer response to neoadjuvant treatment: comparison with tumour regression grade at histology. Eur Radiol. 2013;23(8):2165–74.

    PubMed  Google Scholar 

  20. Li J, Yan LL, Zhang HK, Wang Y, Xu SN, Li HL, et al. Dynamic contrast-enhanced and diffusion-weighted MR imaging in early prediction of pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer. Abdom Radiol (NY). 2022;47(10):3394–405.

    PubMed  Google Scholar 

  21. Li J, Xu SN, Wang Y, Ma F, Chen XJ, Qu JR. Spectral CT vs. diffusion-weighted imaging for the quantitative prediction of pathologic response to neoadjuvant chemotherapy in locally advanced gastric cancer. Eur Radiol. 2024;34(9):6193–204.

    CAS  PubMed  Google Scholar 

  22. Giganti F, Orsenigo E, Esposito A, Chiari D, Salerno A, Ambrosi A, et al. Prognostic role of diffusion-weighted MR imaging for resectable gastric cancer. Radiology. 2015;276(2):444–52.

    PubMed  Google Scholar 

  23. Zhu YJ, Zhou YT, Zhang W, Xue LY, Li Y, Jiang J, et al. Value of quantitative dynamic contrast-enhanced and diffusion-weighted magnetic resonance imaging in predicting extramural venous invasion in locally advanced gastric cancer and prognostic significance. Quant Imaging Med Surg. 2021;11(1):328–40.

    PubMed  PubMed Central  Google Scholar 

  24. Zhu YJ, Jiang ZC, Wang BZ, Li Y, Jiang J, Zhong YX, et al. Quantitative dynamic-enhanced MRI and intravoxel incoherent motion diffusion-weighted imaging for prediction of the pathological response to neoadjuvant chemotherapy and the prognosis in locally advanced gastric cancer. Front Oncol. 2022;12:841460.

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Liu S, Guan WX, Wang H, Pan L, Zhou ZP, Yu HP, et al. Apparent diffusion coefficient value of gastric cancer by diffusion-weighted imaging: correlations with the histological differentiation and Lauren classification. Eur J Radiol. 2014;83(12):2122–8.

    PubMed  Google Scholar 

  26. Curvo-Semedo L, Lambregts DM, Maas M, Beets GL, Caseiro-Alves F, Beets-Tan RG. Diffusion-weighted MRI in rectal cancer: apparent diffusion coefficient as a potential noninvasive marker of tumor aggressiveness. J Magn Reson Imaging. 2012;35(6):1365–71.

    PubMed  Google Scholar 

  27. Zhong X, Tang HS, Guan TP, Lu BG, Zhang CJ, Tang DL, et al. Added value of quantitative apparent diffusion coefficients for identifying small hepatocellular carcinoma from benign nodule categorized as LI-RADS 3 and 4 in cirrhosis. J Clin Transl Hepatol. 2022;10(1):34–41.

    PubMed  Google Scholar 

  28. Zhong X, Li L, Yin JX, Chen YL, Xin X, Yu LL, et al. Reproducibility and usefulness of quantitative apparent diffusion coefficient measurements for predicting program death-ligand 1 expression in nasopharyngeal carcinoma. Cancer Imaging. 2023;23(1):98.

    PubMed  PubMed Central  Google Scholar 

  29. De Felice F, Malerba S, Nardone V, Salvestrini V, Calomino N, Testini M, et al. Progress and challenges in integrating nutritional care into oncology practice: results from a National survey on behalf of the nutrionc research group. Nutrients. 2025;17(1):188.

    PubMed  PubMed Central  Google Scholar 

  30. Liu S, Zheng HH, Zhang YJ, Chen L, Guan WX, Guan Y, et al. Whole-volume apparent diffusion coefficient-based entropy parameters for assessment of gastric cancer aggressiveness. J Magn Reson Imaging. 2018;47(1):168–75.

    PubMed  Google Scholar 

  31. Jacquet P, Sugarbaker PH. Clinical research methodologies in diagnosis and staging of patients with peritoneal carcinomatosis. Cancer Treat Res. 1996;82:359–74.

    CAS  PubMed  Google Scholar 

  32. Lei ZY, Wang JH, Li Z, Li BZ, Luo JL, Wang XJ, et al. Hyperthermic intraperitoneal chemotherapy for gastric cancer with peritoneal metastasis: A multicenter propensity score-matched cohort study. Chin J Cancer Res. 2020;32(6):794–803.

    PubMed  PubMed Central  Google Scholar 

  33. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–74.

    CAS  PubMed  Google Scholar 

  34. Nakamura K, Joja I, Nagasaka T, Fukushima C, Kusumoto T, Seki N, et al. The mean apparent diffusion coefficient value (ADCmean) on primary cervical cancer is a predictive marker for disease recurrence. Gynecol Oncol. 2012;127(3):478–83.

    PubMed  Google Scholar 

  35. Matsumoto Y, Kuroda M, Matsuya R, Kato H, Shibuya K, Oita M, et al. In vitro experimental study of the relationship between the apparent diffusion coefficient and changes in cellularity and cell morphology. Oncol Rep. 2009;22(03):641–8.

    PubMed  Google Scholar 

  36. Mori N, Ota H, Mugikura S, Takasawa C, Tominaga J, Ishida T, et al. Detection of invasive components in cases of breast ductal carcinoma in situ on biopsy by using apparent diffusion coefficient MR parameters. Eur Radiol. 2013;23(10):2705–12.

    PubMed  Google Scholar 

  37. Kim JY, Kim JJ, Hwangbo L, Kang T, Park H. Diffusion-weighted imaging of invasive breast cancer: relationship to distant metastasis-free survival. Radiology. 2019;291(2):300–7.

    PubMed  Google Scholar 

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Acknowledgements

We would like to thank the native English speaking scientists of Elixigen Company (Huntington Beach, California) for editing our manuscript.

Funding

This work was supported by the Key-Area Research and Development Program of Guangzhou City [grant number 2023B01J1001].

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Author notes

  1. Xin Xin and Yongfang Tang contributed equally to this work.

Authors and Affiliations

  1. Department of Medical Imaging, Guangzhou Institute of Cancer Research, the Affiliated Cancer Hospital, Guangzhou Medical University, Guangzhou, China

    Xin Xin, Yongfang Tang, Man Lu, Jie Huang, Jian Shang, Lidan Yang, Lihuan Dai, Jinxue Yin, Jiansheng Li & Xi Zhong

  2. Department of Abdominal Surgery, Guangzhou Institute of Cancer Research, the Affiliated Cancer Hospital, Guangzhou Medical University, Guangzhou, China

    Hongsheng Tang

  3. Department of Oncology Institute, Guangzhou Institute of Cancer Research, the Affiliated Cancer Hospital, Guangzhou Medical University, Guangzhou, China

    Qibin Leng

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Contributions

X.Z, Q.B.L, and H.S.T contributed to the conception and design of the work and funding acquisition. X.X and Y.F.T carried out the investigation and drafted the manuscript. M.L, J.H, and L.D.Y collected the MRI and clinical data. J.S and J.X.Y performed ADC value measurements. L.H.D and J.S.L verified the data and conducted the statistical analyses. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Qibin Leng, Hongsheng Tang or Xi Zhong.

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This study was approved by the Institutional Review Board of Affiliated Cancer Hospital & Institute of Guangzhou Medical University. Experiments on humans and/or the use of human tissue samples must confirm that all experiments were performed in accordance with relevant guidelines and regulations.

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Not applicable.

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The authors declare no competing interests.

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Xin, X., Tang, Y., Lu, M. et al. Prognostic value of diffusion-weighted imaging to cytoreductive surgery with or without hyperthermic intraperitoneal chemotherapy for patients with gastric cancer and peritoneal metastases. BMC Cancer 25, 616 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12885-025-14008-z

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Keywords

BMC Cancer

ISSN: 1471-2407

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