Peng Fei Gao
Na Lu2
Wen Liu- 1Department of Traditional Chinese medicine, Jinshan Hospital, Fudan University, Shanghai, China
- 2Department of Radiology, Huashan Hospital North, Fudan University, Shanghai, China
- 3Department of Radiology, Jinshan Hospital, Fudan University, Shanghai, China
Aim: In this study, we aimed to compare the diagnostic values of MRI and FDG-PET for the prediction of the response to neoadjuvant chemoradiotherapy (NACT) of patients with locally advanced Rectal cancer (RC).
Methods: Electronic databases, including PubMed, Embase, and the Cochrane library, were systematically searched through December 2021 for studies that investigated the diagnostic value of MRI and FDG-PET in the prediction of the response of patients with locally advanced RC to NACT. The quality of the included studies was assessed using QUADAS. The pooled sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR), and the area under the ROC (AUC) of MRI and FDG-PET were calculated using a bivariate generalized linear mixed model, random-effects model, and hierarchical regression.
Results: A total number of 74 studies with recruited 4,105 locally advanced RC patients were included in this analysis. The pooled sensitivity, specificity, PLR, NLR, and AUC for MRI were 0.83 (95% CI: 0.77–0.88), 0.85 (95% CI: 0.79–0.89), 5.50 (95% CI: 4.11-7.35), 0.20 (95% CI: 0.14–0.27), and 0.91 (95% CI: 0.88–0.93), respectively. The summary sensitivity, specificity, PLR, NLR and AUC for FDG-PET were 0.81 (95% CI: 0.77-0.85), 0.75 (95% CI: 0.70–0.80), 3.29 (95% CI: 2.64–4.10), 0.25 (95% CI: 0.20–0.31), and 0.85 (95% CI: 0.82–0.88), respectively. Moreover, there were no significant differences between MRI and FDG-PET in sensitivity (P = 0.565), and NLR (P = 0.268), while the specificity (P = 0.006), PLR (P = 0.006), and AUC (P = 0.003) of MRI was higher than FDG-PET.
Conclusions: MRI might superior than FGD-PET for the prediction of the response of patients with locally advanced RC to NACT.
Introduction
Rectal cancer (RC) as is a common malignant tumor, with nearly 39,910 new cases in US annually (1, 2). Currently, surgical resection is the main curative method for patients with early-stage RC, whereas nearly 55% of RC cases are diagnosed at stage II or higher, when additional treatment strategies are needed (3, 4). Neoadjuvant chemoradiotherapy (NACT), total mesorectal excision, and postoperative chemotherapy are standard treatment strategies in patients with locally advanced RC (5, 6). Earlier studies showed that NACT improved locoregional control with significant pathologic complete response (pCR), which was defined as the absence of viable tumor cells established by pathologic examination (7–10). The tumor responses to NACT ranged from sustained tumor progression to complete remission, and adjuvant postoperative therapy could affect by the heterogeneity of patients’ tumor response to NACT. Previous evidence indicated that surgery could be omitted in patients with pCR to NACT, in which the watch-and-wait strategy was associated with better prognosis (11, 12). Therefore, the accurate assessment of the response to NACT could contribute to more effective clinical care aimed at personalized treatment strategy in patients with locally advanced RC.
Recent studies established the role of imaging modalities, including fluorine-18 fluorodeoxyglucose-positron emission tomography (18FDG-PET), irrespective whether combined with computed tomography (CT) or MRI in the prediction of the response to NACT (13, 14). The apparent diffusion coefficient (ADC), measured by MRI, could facilitate tumor cellularity and cell membrane integrity which are sensitive to intratumoral changes induced by NACT. MRI was found to have a relatively better predictive value for the tumor response during and after neoadjuvant therapy (15). FDG-PET has been widely used for the diagnosis of recurrent or metastatic colorectal cancer (CRC), with a detection accuracy rate for pelvic recurrence within 74%–96% (16–18). 18FDG-PET combined with CT (FDG-PET/CT) showed an even higher accuracy rate for diagnosing locally recurrent and metastatic CRC (19, 20). Several studies revealed that FDG-PET predicted successfully the response to NACT, while the predictive value between MRI and FDG-PET for the response to NACT in locally advanced RC patients remains controversial. Therefore, here, we performed a meta-analysis focused on indirect comparisons between the diagnostic values of MRI and FDG-PET for the assessment of the response to NACT.
Materials and methods
Data sources, search strategy, and selection criteria
This review was conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement issued in 2009 (21). Studies that had investigated the diagnostic value of MRI or FDG-PET for the assessment of the response to NACT in patients with locally advanced RC were eligible for inclusion in this analysis, with no restrictions placed on the publication language and status. The PubMed, Embase, and Cochrane Library electronic databases were searched for articles published through December 2021. The following search terns were used: “Magnetic Resonance Imaging” OR “Positron-Emission Tomography” OR “computed tomography” AND “rectal cancer” AND “preoperative” OR “neoadjuvant”. The details of searching strategy in PubMed are specified in Supplemental 1. We also conducted manual searches of the reference lists of all relevant original and review articles to identify additional eligible studies.
The literature search and study selection were independently performed by two authors using a standardized approach. Any inconsistencies between authors were settled by consultation and discussion with an additional author until a consensus was reached. The following inclusion criteria were applied: (1) Study design: prospective or retrospective design; (2) Participants: all patients were diagnosed with locally advanced RC by pathologic examination; (3) Diagnostic tool: MRI, FDG-PET, or FDG-PET/CT; (4) Gold reference: tumor response diagnosed using the postoperative histological results; and (5) Outcomes: true and false positive, true and false negative, or data could be transformed into the aforementioned information data.
Data collection and quality assessment
The data collection and quality assessment were conducted by two authors, and the information collected was examined and adjudicated by an additional author. The data collected included the first author’s surname, publication year, country, study design, sample size, median or mean age, number of men and women included, preoperative regimen, diagnostic tool, responders and non-responders, true and false positive, and true and false negative. The quality of the included studies was assessed using QUADAS, based on 14 items; “yes”, “no”, or “unclear” were the possible answers to each question/item. A study that had collected 12 or more “yes” answers was regarded to have high quality, and those that received 10–12 “yes” answers for were considered to be of moderate quality.
Statistical analysis
The sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and the area under the receiver operating characteristic curves (AUC) with corresponding 95% confidence intervals (CIs) were calculated based on true positive, false positive, false negative, and true negative results in each individual study before data pooling. Then, the pooled sensitivity, specificity, PLR, NLR, and AUC for each diagnostic tool were calculated using a bivariate generalized linear mixed model, random-effects model, and hierarchical regression (22–24). Heterogeneity across the included studies was evaluated by I2 and Q statistic; P < 0.10 was considered to indicate significant heterogeneity (25). Subgroup analyses for sensitivity, specificity, PLR, NLR, and AUC were conducted based on the study design (retrospective or prospective), sample size (>50 and <50), and mean age (>60.0 and <60.0). The ratio of between the MRI and FDG-PET diagnostic parameters in the subgroups were calculated for indirect comparison of between the MRI and FDG-PET diagnostic values (26). The publication biases for CT and FDG-PET were assessed using funnel plots and Deeks’ asymmetry tests (27). The P-value for all pooled analyses were two-sided; P < 0.05 was considered to indicate statistically significant differences. Stata software (version 10.0; Stata Corporation, College Station, TX, USA) was employed to conduct all statistical analyses.
Results
Literature search
The results of the study-selection process are depicted in Figure 1. We initially identified 2946 potentially eligible articles after the original electronic search. Of these, 2539 articles were excluded during an initial review of the titles. Abstracts assessment for 407 articles, and 278 studies were excluded due to the use of other diagnostic tools and review designs. The remaining 129 studies were subjected to further tests to identify any other potential studies eligible for inclusion, and 74 of them satisfied the inclusion criteria and were ultimately included in the quantitative analysis (28–101). A manual search of the reference lists contained within these studies did not yield any new eligible studies. The general characteristics of the included studies are presented in Table 1.
Figure 1 Flow diagram of the study selection process.
Table 1 The baseline characteristics of included studies.
Study characteristics
Seventy-four studies with a total number of 4,105 patients with locally advanced RC were included in this analysis. Forty-five studies were designed as prospective, whereas the remaining 29 studies were designed as retrospective. The mean age of the patients was 49.5–71.5 years; 12–146 individuals were included in each of the included studies. Seventy studies employed radiochemotherapy as preoperative regimen, whereas radiotherapy or chemotherapy was used as preoperative regimen in the remaining four studies. The predictive value of MRI for the response to NACT was established in 41 studies, the predictive value of FDG-PET in 9 studies, and the predictive value of FDG-PET/CT in 29 studies. Seventeen of included studies were of high quality, whereas the remaining 57 studies were of moderate quality.
MRI
The sensitivity and specificity are presented in Figure 2. The pooled sensitivity and specificity of MRI for predicting the response to NACT were 0.83 (95% CI: 0.77–0.88) and 0.85 (95% CI: 0.79–0.89), respectively. Substantial heterogeneity in the sensitivity (I2 =76.46%; P<0.01) and specificity (I2 =90.76%; P<0.01) of the included studies was observed. Moreover, the summarized PLR and NLR of MRI for predicting the response to NACT were 5.50 (95% CI: 4.11–7.35) and 0.20 (95% CI: 0.14–0.27), respectively (Figure 3), with significant heterogeneity in PLR (I2 =90.17%; P<0.01) and NLR (I2 =86.70%; P<0.01) across the included studies. In addition, the summarized AUC of MRI for predicting the response to NACT was 0.91 (95% CI: 0.88–0.93; Figure 4). Finally, there was no significant publication bias for MRI (P = 0.89; Figure 5).
Figure 2 Pooled sensitivity and specificity of MRI.
Figure 3 Pooled PLR and NLR of MRI.
Figure 4 Summarized ROC curve and AUC for MRI.
Figure 5 Publication biases for MRI.
FDG-PET
The summarized sensitivity and specificity are illustrated in Figure 6. The pooled sensitivity and specificity of FDG-PET for predicting the response to NACT were 0.81 (95% CI: 0.77–0.85) and 0.75 (95% CI: 0.70–0.80), respectively. Significant heterogeneity was detected in the sensitivity (I2 =49.40%; P<0.01) and specificity (I2 =80.77%; P<0.01) of FDG-PET. Moreover, the pooled PLR and NLR of FDG-PET for predicting the response to NACT were 3.29 (95% CI: 2.64–4.10) and 0.25 (95% CI: 0.20–0.31) respectively, with substantial heterogeneity for PLR (I2 =78.03%; P<0.01) and NLR (I2 =51.41%; P<0.01) across the included studies (Figure 7). In addition, the summary AUC of FDG-PET was 0.85 (95% CI: 0.82–0.88; Figure 8). Finally, no significant publication bias was observed in FDG-PET (P = 0.12; Figure 9).
Figure 6 Pooled sensitivity and specificity of FDG-PET and FDG-PET/CT.
Figure 7 Pooled PLR and NLR of FDG-PET and FDG-PET/CT.
Figure 8 Summarized ROC curve and AUC for FDG-PET and FDG-PET/CT.
Figure 9 Publication biases for FDG-PET and FDG-PET/CT.
Indirect comparison of MRI and FDG-PET
The indirect comparison of the predictive values of MRI and FDG-PET for the response to NACT were calculated, the results of which suggested no significant differences between MRI and FDG-PET or FDG-PET/CT for the response to neoadjuvant chemoradiotherapy in patients with locally advanced RC, in terms of sensitivity (ratio: 1.02; 95% CI: 0.94–1.11; P = 0.565), and NLR (ratio: 0.80; 95% CI: 0.54–1.19; P = 0.268). Moreover, we noted the specificity (ratio: 1.13; 95% CI: 1.04–1.24; P = 0.006), PLR (ratio: 1.67; 95% CI: 1.16–2.41; P = 0.006), and AUC (ratio: 1.07; 95% CI: 1.02–1.12; P = 0.003).
Meta-regression and subgroup analyses
The results of our meta-regression analyses showed that the sample size and mean age affected the sensitivity of MRI, whereas the study design did not affect MRI sensitivity. Moreover, the study design, sample size, and mean age did not affect the specificity of MRI. No bias was established in the sensitivity and specificity of FDG-PET exerted by study design, sample size, and mean age (Supplemental 2). The results of the subgroup analyses regarding the sensitivity, specificity, PLR, NLR, and AUC of MRI and FDG-PET are presented in Table 2. We noted a higher specificity in patients that had received MRI than in those subjected to FDG-PET if pooled retrospective studies (P = 0.010), at a sample size > 50 (P = 0.046). Furthermore, MRI had a higher PLR than FDG-PET when the pooled study was designed as retrospective (P = 0.003), with a sample size > 50 (P = 0.027) and a mean age of the patients > 60.0 years (P = 0.013). Finally, MRI was associated with lower NLR than FDG-PET if mean age of the patients > 60.0 years (P = 0.033).
Table 2 Subgroup analyses for diagnostic parameters.
Discussion
The present meta-analysis was based on published studies and investigated the predictive value of MRI and FDG-PET for the response to NACT of patients with locally advanced RC. This comprehensive, quantitative study included 74 studies with 4,105 patients with a wide range of patients’ characteristics. Our findings suggest that MRI and FDG-PET had a moderate predictive value for the response to NACT. Moreover, the predictive value of MRI might be superior to that of FDG-PET, in terms of specificity, PLR, and AUC. Finally, the predictive value of MRI and FDG-PET for predicting the response to NACT of patients with locally advanced RC could affect by sample size, and mean age.
A previous meta-analysis of 33 studies was conducted to compare the predictive value of MRI and FDG-PET for the pathological response to NACT in patients with RC (102). Its authors found that MRI was superior to FDG-PET in predicting the pathological response to NACT, whereas the specificity and positive predictive value of MRI was relatively lower, especially in patients with mucinous-type rectal adenocarcinomas. However, several studies were not included in this analysis, and indirect comparisons of MRI and FDG-PET were not performed. Moreover, an important meta-analysis evaluated the diagnostic performance of MRI, endorectal ultrasonography, and CT in predicting the response to preoperative therapy for patients with locally advanced RC based on 46 studies. They suggested MRI, endorectal ultrasonography, and CT could not used to predict complete response to NACT, and the positive predictive value for above imaging techniques was low for evaluated the tumor invasion in the circumferential resection margin. Furthermore, the diagnostic accuracy of MRI, endorectal ultrasonography, and CT for the prediction of metastatic lymph node disease was low. However, the study pooled only the diagnostic parameters for each diagnostic tool, and no comparisons of these imaging techniques were conducted. In addition, no stratification of analyses based on study or patients’ characteristics was conducted (103). Therefore, the current meta-analysis was performed to compare the diagnostic value of MRI and FDG-PET for the response to NACT in patients with locally advanced RC.
The summarized diagnostic parameters of MRI were higher than those of FDG-PET in terms of sensitivity, specificity, PLR, and AUC; the NLR of MRI was lower than that of FDG-PET. Moreover, the diagnostic values of MRI and FDG-PET were moderate for the response to NACT. Moreover, an indirect comparisons results indicated MRI were associated with higher specificity, PLR, and AUC than FDG-PET. Nevertheless, these results require further prospective research for a more comprehensive update of the diagnostic values of MRI and FDG-PET for the response to NACT. Several advantages of MRI should be mentioned: (1) The application of MRI in patients with locally RC without ionizing radiation prevents the stimulation of tumor progression by ionizing radiation; (2) The ancillary equipment of cyclotron is not installed nearby, which is associated with a lower cost than that of FDG-PET/CT application (104); and (3) The examination time in MRI was shorter than that in FDG-PET/CT (105). Therefore, MRI should be largely employed for preoperative evaluation in patients with RC.
To explore the sources of substantial heterogeneity, meta-regression and subgroup analyses were conducted based on the study design, sample size, and mean age of patients. The results of the meta-regression analyses indicated that the sample size and the mean age might have contributed to a significant heterogeneity in the sensitivity of MRI. Moreover, our subgroup analyses indicated that MRI was superior to FDG-PET when the pooled study was designed as retrospective, with a larger sample size, and a mean age of patients > 60.0 years. The potential reasons for this discrepancy could the evidence level, weighted based on the overall analyses and the tumor stages are affecting by mean age.
Several strengths of our study should be highlighted. First, the large sample size allowed us to quantitatively compare the predictive values of MRI and FDG-PET for the response to NACT in patients with locally advanced RC. Thus, our findings are potentially more robust than those of any other earlier individual study. Second, the consistency of the findings of this investigation and the lack of significant publication bias also support the robustness of our present findings. Third, indirect comparisons of the predictive value of MRI and FDG-PET were conducted to provide a better imaging tool for the response to NACT. Finally, the present study provides evidence for evaluation of the diagnostic values of MRI and FDG-PET in patients with specific characteristics.
The limitations of our study are as follows: (1) A study designed as retrospective was included in this analysis, which might have introduced uncontrolled bias; (2) Inconsistencies in the characteristics were present among the included studies, especially in terms of tumor properties, which were not reported in most of the included studies; (3) The heterogeneity across included studies were not fully explained by subgroup analyses; (4) Although the imaging examination were performed after NACT and before surgery, while the exact timing of the scanning might play an important role on the diagnostic ability of MRI and FDG-PET; (5) Although our results indicated no significant publication bias, this study was based on published articles, and publication bias was inevitable; and (6) Stratified analyses based on additional characteristics of patients were not conducted since this information was not available.
Conclusion
The results of this study show that MRI and FDG-PET have a moderate diagnostic ability for the response of patients with locally advanced RC to NACT. The results of our indirect analyses suggested MRI was associated with elevated specificity, PLR, and AUC than FDG-PET. Subgroup analyses indicated that the predictive value of MRI was superior to that FDG-PET when the pooled study was designed as retrospective, with a large sample size, and a mean age of the patients > 60.0 years. These results add to the existing evidence but need further prospective research that would perform direct comparisons between the predictive values of MRI and FDG-PET for the response of patients with locally advanced RC to NACT.
Author contributions
PG performed data acquisition, analysis, and interpretation, drafted the article, and obtaining the final approval. NL was responsible for data acquisition, analysis, and interpretation, drafting of the article, and obtaining the final approval. WL developed the conception and design of the study, conducted critical revision, and participated in obtaining the final approval. All authors contributed to the article and approved the submitted version.
Funding
The study was supported by National Natural Science Foundations of China (Grant No. 81701686) and Shanghai Municipal Commission of Health (Grant No. ZK2019B01).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fonc.2023.1031581/full#supplementary-material
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Keywords: rectal cancer, diagnostic value, MRI, FDG-PET, FDG-PET/CT, neoadjuvant therapy, response
Citation: Gao PF, Lu N and Liu W (2023) MRI VS. FDG-PET for diagnosis of response to neoadjuvant therapy in patients with locally advanced rectal cancer. Front. Oncol. 13:1031581. doi: 10.3389/fonc.2023.1031581
Received: 30 August 2022; Accepted: 02 January 2023;
Published: 18 January 2023.
Edited by:
Cornelis F.M. Sier, Leiden University, NetherlandsReviewed by:
Shang Wan, Sichuan University, ChinaAlexander Heriot, Peter MacCallum Cancer Centre, Australia
Copyright © 2023 Gao, Lu and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Wen Liu, liuwenwenliu5th@163.com