Lymph Node Regression to Neoadjuvant Chemoradiotherapy in Patients with Locally Advanced Rectal Cancer: Prognostic Implication and a Predictive Model

Preoperative inflammatory markers and tumor markers in predicting lymphatic metastasis and postoperative complications in colorectal cancer: a retrospective study

OBJECTIVE

To analyze the impact of preoperative inflammatory markers and tumor markers on lymphatic metastasis and postoperative complications in colorectal cancer patients, and explore their predictive value for these outcomes. Furthermore, based on the preoperative inflammatory and tumor marker indicators with significant effects, predictive models for the risk of lymphatic metastasis and the incidence of postoperative complications will be constructed.

METHODS

This study retrospectively analyzed the clinical data of CRC patients who underwent surgical treatment at Shanxi Bethune Hospital between January 2021 and June 2024. Preoperative inflammatory markers and tumor markers were compared between the lymph node-positive and lymph node-negative groups. Variables were selected using Lasso regression, and independent factors influencing lymph node metastasis were identified through multivariate logistic regression analysis. Based on these results, a Nomogram prediction model was constructed, and its accuracy was evaluated using a calibration curve. The discriminatory ability of the model was assessed with the ROC curve, and its clinical applicability was analyzed using the DCA curve. Similarly, for predicting postoperative complications, Pearson correlation analysis was used to examine the relationships between preoperative inflammatory markers, tumor markers, and complications. ROC curves were employed to calculate the AUC and optimal cutoff values for each marker. Kaplan-Meier (KM) curves were used to analyze the impact of these markers on DFS. Independent factors were identified through univariate and multivariate logistic regression analyses, and a Nomogram model was constructed and validated.

RESULTS

A total of 196 patients were included in the study. The NLR, PLR, FAR, CEA, CA199, and CA724 levels were significantly elevated in the lymph node metastasis group (P < 0.05). Lasso regression identified smoking history, NLR, FAR, and CA724 as non-zero coefficient variables. Multivariate logistic regression further confirmed smoking history (HR = 4.20), NLR (HR = 2.52), FAR (HR = 1.18), and CA724 (HR = 1.32) as independent predictors of lymph node metastasis (P < 0.05). The Nomogram prediction model constructed based on these results showed high prediction accuracy, with a ROC curve AUC of 0.880, indicating excellent discriminatory ability. The DCA decision curve demonstrated good clinical applicability. In postoperative complication prediction, Pearson correlation analysis revealed a positive correlation between NLR, PLR, FAR, CA199, and CA724 with complication rates (P < 0.05), with correlation coefficients of 0.24, 0.34, 0.16, 0.19, and 0.19, respectively, with PLR showing the strongest correlation. ROC curve analysis showed that the AUCs for NLR, PLR, LMR, FAR, and CAR were 0.633, 0.675, 0.467, 0.580, and 0.559, with optimal cutoff values of 4.29, 261.71, 3.39, 18.20, and 11.26, respectively. The AUCs for CEA, CA199, and CA724 were 0.567, 0.612, and 0.609, with optimal cutoff values of 11.87, 10.27, and 6.85. KM curve analysis showed that higher levels of NLR, FAR, CAR, CEA, CA199, and CA724 were associated with poorer DFS. Univariate and multivariate logistic regression further confirmed NLR (HR = 1.53) and CA724 (HR = 1.11) as independent predictors of complications (P < 0.05). The calibration curve indicated high prediction accuracy, with a ROC curve AUC of 0.729, demonstrating excellent discriminatory ability, and the DCA decision curve showed good clinical applicability.

CONCLUSION

Preoperative inflammatory markers and tumor markers have a significant impact on the occurrence of lymphatic metastasis and postoperative complications in colorectal cancer patients, demonstrating certain clinical value in predicting lymphatic metastasis and postoperative complications. The predictive models developed in this study provide a reference for personalized diagnosis and treatment, but their practical application needs to be further validated through large-scale clinical studies.

Prognostic Value of Tumor Regression Grade Combined with Pathological Lymph Node Status in Initially Node-Positive Rectal Cancer Treated with Neoadjuvant Chemoradiotherapy

BACKGROUND

The prognostic value of tumor regression grade (TRG) after neoadjuvant chemoradiotherapy for rectal cancer is inconsistent in the literature. Both TRG and post-therapy lymph node (ypN) status could reflect the efficacy of neoadjuvant therapy. Here, we explored whether TRG combined with ypN status could be a prognostic factor for MRI-based lymph node-positive (cN+) rectal cancer following neoadjuvant chemoradiotherapy.

METHODS

671 cN + rectal cancer patients who received neoadjuvant chemoradiotherapy followed by radical resection were enrolled. Patients were innovatively divided into three groups based on TRG and ypN status: TRG0-1N0, TRG2-3N0 or TRG0-1N+, TRG2-3N+. Kaplan-Meier method and log-rank test were used to compare the disease-free survival (DFS) and overall survival (OS) among three groups. Univariate and multivariate analyses were performed to explore the prognostic value of the modified TRG in cN + rectal cancer following neoadjuvant chemoradiotherapy.

RESULTS

The mean duration of follow-up was 30.4 months. Significant survival differences were observed among the three groups. The 3-year DFS were 83.0%, 69.2% and 55.9%, respectively. The 5-year OS were 83.5%, 80.4% and 57.8%, respectively. TRG combined with ypN status was an independent predictor for both DFS and OS in multivariate analysis.

CONCLUSION

TRG combined with ypN status is a novel prognostic factor in cN + rectal cancer following neoadjuvant chemoradiotherapy, which assists clinicians make appropriate decisions regarding postoperative treatment and surveillance.

A nomogram of inflammatory indexes for preoperatively predicting the risk of lymph node metastasis in colorectal cancer

PURPOSE

To investigate the independent risk factors associated with the development of lymph node metastasis (LNM) in patients with colorectal cancer (CRC), focusing on preoperative systemic inflammatory indicators, and to construct a corresponding risk predictive model.

MATERIALS AND METHODS

The clinical data of 241 patients with CRC who underwent surgery after the first diagnosis between January 2012 and December 2017 at our hospital were reviewed. A best logistic regression model was constructed by Lasso regression for multivariate analysis, from which a Nomogram was derived. Using bootstrap to conduct internal validation. The model's predictive performance and clinical practicability were evaluated using the receiver operating characteristic curve (ROC) curve, calibration curve, and decision curve analysis (DCA). External validation was conducted using retrospective data from 170 patients who underwent surgery between January 2020 and May 2022 at another hospital.

RESULTS

Cross-validation indicated smoking history, neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), fibrinogen-albumin ratio (FAR), and fecal occult blood (FOB) as variables with non-zero coefficients. These factors were included in the logistic regression, and multivariate analysis confirmed that smoking history, NLR, LMR, FAR, and FOB were independent risk factors (P < 0.05). The ROC and calibration curve of the original model and external validation indicated strong predictive power of the model. DCA suggested the model's favorable clinical utility.

CONCLUSIONS

The model constructed in this study has robust predictive performance and clinical utility for the preoperative determination of CRC LMN, offering significant for clinical decision-making in patients with CRC.

Machine learning to predict distant metastasis and prognostic analysis of moderately differentiated gastric adenocarcinoma patients: a novel focus on lymph node indicators

Background

Moderately differentiated gastric adenocarcinoma (MDGA) has a high risk of metastasis and individual variation, which strongly affects patient prognosis. Using large-scale datasets and machine learning algorithms for prediction can improve individualized treatment. The specific efficacy of several lymph node indicators in predicting distant metastasis (DM) and patient prognosis in MDGA remains obscure.

Methods

We collected data from MDGA patients from the SEER database from 2010 to 2019. Additionally, we collected data from MDGA patients in China. We used nine machine learning algorithms to predict DM. Subsequently, we used Cox regression analysis to determine the risk factors affecting overall survival (OS) and cancer-specific survival (CSS) in DM patients and constructed nomograms. Furthermore, we used logistic regression and Cox regression analyses to assess the specific impact of six lymph node indicators on DM incidence and patient prognosis.

Results

We collected data from 5,377 MDGA patients from the SEER database and 109 MDGC patients from hospitals. T stage, N stage, tumor size, primary site, number of positive lymph nodes, and chemotherapy were identified as independent risk factors for DM. The random forest prediction model had the best overall predictive performance (AUC = 0.919). T stage, primary site, chemotherapy, and the number of regional lymph nodes were identified as prognostic factors for OS. Moreover, T stage, number of regional lymph nodes, primary site, and chemotherapy were also influential factors for CSS. The nomograms showed good predictive value and stability in predicting the 1-, 3-, and 5-year OS and CSS in DM patients. Additionally, the log odds of a metastatic lymph node and the number of negative lymph nodes may be risk factors for DM, while the regional lymph node ratio and the number of regional lymph nodes are prognostic factors for OS.

Conclusion

The random forest prediction model accurately identified high-risk populations, and we established OS and CSS survival prediction models for MDGA patients with DM. Our hospital samples demonstrated different characteristics of lymph node indicators in terms of distant metastasis and prognosis.

Multiparametric MRI-based radiomic model for predicting lymph node metastasis after neoadjuvant chemoradiotherapy in locally advanced rectal cancer

OBJECTIVES

To construct and validate multiparametric MR-based radiomic models based on primary tumors for predicting lymph node metastasis (LNM) following neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC) patients.

METHODS

A total of 150 LARC patients from two independent centers were enrolled. The training cohort comprised 100 patients from center A. Fifty patients from center B were included in the external validation cohort. Radiomic features were extracted from the manually segmented volume of interests of the primary tumor before and after nCRT. Feature selection was performed using multivariate logistic regression analysis. The clinical risk factors were selected via the least absolute shrinkage and selection operator method. The radiologist's assessment of LNM was performed. Eight models were constructed using random forest classifiers, including four single-sequence models, three combined-sequence models, and a clinical model. The models' discriminative performance was assessed via receiver operating characteristic curve analysis quantified by the area under the curve (AUC).

RESULTS

The AUCs of the radiologist's assessment, the clinical model, and the single-sequence models ranged from 0.556 to 0.756 in the external validation cohort. Among the single-sequence models, modelpost_DWI exhibited superior predictive power, with an AUC of 0.756 in the external validation set. In combined-sequence models, modelpre_T2_DWI_post had the best diagnostic performance in predicting LNM after nCRT, with a significantly higher AUC (0.831) than those of the clinical model, modelpre_T2_DWI, and the single-sequence models (all p < 0.05).

CONCLUSIONS

A multiparametric model that incorporates MR radiomic features before and after nCRT is optimal for predicting LNM after nCRT in LARC.

CRITICAL RELEVANCE STATEMENT

This study enrolled 150 LARC patients from two independent centers and constructed multiparametric MR-based radiomic models based on primary tumors for predicting LNM following nCRT, which aims to guide therapeutic decisions and predict prognosis for LARC patients.

KEY POINTS

The biological characteristics of primary tumors and metastatic LNs are similar in rectal cancer. Radiomics features and clinical data before and after nCRT provide complementary tumor information. Preoperative prediction of LN status after nCRT contributes to clinical decision-making.

Comparative analysis of preoperative chemoradiotherapy and upfront surgery in the treatment of upper-half rectal cancer: oncological benefits, surgical outcomes, and cost implications

The value of neoadjuvant chemoradiotherapy (CRT) is not absolutely clear for upper-half (> 7-15 cm) rectal cancer. This study aimed to compare the efficacy and safety of radical surgery with preoperative CRT vs. upfront surgery (US) in Chinese patients with stage II and III upper-half rectal cancer. A total of 809 patients with locally advanced upper-half rectal cancer between 2017 and 2021 were enrolled retrospectively (280 treated with CRT and 529 treated with US). Through 1:1 propensity score matching, the CRT (172 patients) and US (172 patients) groups were compared for short-term postoperative results and long-term oncological and functional outcomes. In the entire cohort, patients in the CRT group had a younger age, lower distance from the anal verge (DAV), and higher rates of cT4 stage, cN2 stage, mrCRM positivity, EMVI positivity, CEA elevation, and CA-199 elevation than those in the US group. The 5-year disease-free survival (DFS) was lower in the CRT group than in the US group (76% vs. 84%, p = 0.022), while the 5-year overall survival (OS) was comparable between the two groups (85% and 88%, p = 0.084). The distant metastasis rate was higher in the CRT group than in the US group (12.5% vs. 7.8%, p = 0.028), though the local recurrence rate was similar between the two groups (1.1% and 1.3%, p = 1.000). After performing PSM, the 5-year OS (86% vs. 88% p = 0.312), the 5-year DFS (79% vs. 80%, p = 0.435), the local recurrence rate (1.2% vs. 1.7%, p = 1.000), and the distant metastasis rate (11.0% vs. 9.3%, p = 0.593) were comparable between the two groups. Notable pathological downstaging was observed in the CRT group, with a pathological complete response (PCR) rate of 14.5%. In addition, patients in the CRT group had a lower proportion of pT3 (61.6% vs. 77.9%, p < 0.001), pN + (pN1, 15.1% vs. 30.2%, pN2, 9.3% vs. 20.3%, p < 0.001), stage III (24.4% vs. 50.6%, p < 0.001), perineural invasion (19.8% vs. 32.0%, p = 0.014), and lymphovascular invasion (9.3% vs. 25.6%, p < 0.001) than those in the US group. Postoperative complications and long-term functional results were similar, yet there was a trend toward a higher conversion to laparotomy rate (5 (2.9%) vs. 0 (0.0%), p = 0.061) and higher rates of robotic surgery (11.6% vs. 4.7%, p < 0.001), open surgery (7.0% vs. 0.6%, p < 0.001), diverting stoma (47.1% vs. 25.6%, p < 0.001), and surgery costs (1473.6 ± 106.5 vs. 1140.3 ± 54.3$, p = 0.006) in the CRT group. In addition, EMVI (OR = 2.516, p = 0.001) was the only independent risk factor associated with poor response to CRT, and in subgroup analysis of EMVI + , CRT group patients presented a lower 5-year DFS (72.9% vs. 80.5%, p = 0.025) compared to US group patients. CRT prior to surgery has no additional oncological benefits over US in the treatment of upper-half rectal cancer. In contrast, CRT is associated with increased rates of conversion to laparotomy, stoma creation and higher surgery costs. Surgeons tend to favor robotic surgery in the treatment of complex cases such as radiated upper-half rectal cancers. Notably, EMVI + patients with upper-half rectal cancer should be encouraged to undergo upfront surgery, as preoperative CRT may not provide benefits and may lead to delayed treatment effects.

Lymph node regression after neoadjuvant chemoradiotherapy in rectal cancer

AIMS

Lymph node metastases (LNM) are one of the most important prognostic indicators in solid tumours and a major component of cancer staging. Neoadjuvant therapy might influence nodal status by induction of regression. Our aim is to determine the prevalence and role of regression of LNM on outcomes in patients with rectal cancer.

METHODS AND RESULTS

Four independent study populations of rectal cancer patients treated with similar regimens of chemoradiotherapy were pooled together to obtain a total cohort of 469 patients. Post-treatment nodal status (ypN) and signs of tumour regression (Reg) were incorporated to form three-tiered (ypN- Reg+, ypN- Reg- and ypN+) and four-tiered (ypN- Reg+, ypN- Reg-, ypN+ Reg+ and ypN+ Reg-) classifications. In our cohort, 31% of patients presented with ypN+ rectal cancer. As expected, we found significantly worse overall survival (OS) in ypN+ patients compared to ypN- patients (P = 0.002). The percentage of ypN- patients with lymph nodes with complete regression was 20% in our cohort. While node-negative patients with and without regression had similar OS (P = 0.09), disease-free survival (DFS) was significantly better in node-negative patients with regression (P = 0.009).

CONCLUSIONS

Regression in lymph nodes is frequent, and node-negative patients with evidence of lymph node regression have better DFS compared to node-negative patients without such evidence.

Development and Validation of a Radiomics Model Based on Lymph-Node Regression Grading After Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer

PURPOSE

The response to neoadjuvant chemoradiotherapy (nCRT) varies among patients with locally advanced rectal cancer (LARC), and the treatment response of lymph nodes (LNs) to nCRT is critical in implementing a watch-and-wait strategy. A robust predictive model may help personalize treatment plans to increase the chance that patients achieve a complete response. This study investigated whether radiomics features based on prenCRT magnetic resonance imaging nodes could predict treatment response in preoperative LARC LNs.

METHODS AND MATERIALS

The study included 78 patients with clinical stage T3-T4, N1-2, and M0 rectal adenocarcinoma who received long-course neoadjuvant radiotherapy before surgery. Pathologists evaluated 243 LNs, of which 173 and 70 were assigned to training and validation cohorts, respectively. For each LN, 3641 radiomics features were extracted from the region of interest in high-resolution T2WI magnetic resonance imaging before nCRT. The least absolute shrinkage and selection operator regression model was used for feature selection and radiomics signature building. A prediction model based on multivariate logistic analysis, combining radiomics signature and selected LN morphologic characteristics, was developed and visualized by drawing a nomogram. The model's performance was assessed by receiver operating characteristic curve analysis and calibration curves.

RESULTS

The radiomics signature consists of 5 selected features that were effectively discriminated within the training cohort (area under the curve [AUC], 0.908; 95% CI, 0.857%-0.958%) and the validation cohort (AUC, 0.865; 95% CI, 0.757%-0.973%). The nomogram, which consisted of radiomics signature and LN morphologic characteristics (short-axis diameter and border contours), showed better calibration and discrimination in the training and validation cohorts (AUC, 0.925; 95% CI, 0.880%-0.969% and AUC, 0.918; 95% CI, 0.854%-0.983%, respectively). The decision curve analysis confirmed that the nomogram had the highest clinical utility.

CONCLUSIONS

The nodal-based radiomics model effectively predicts LNs treatment response in patients with LARC after nCRT, which could help personalize treatment plans and guide the implementation of the watch-and-wait approach in these patients.

Implication of MRI Risk Stratification System on the Survival Benefits of Adjuvant Chemotherapy After Neoadjuvant Chemoradiotherapy in Patients With Locally Advanced Rectal Cancer

RATIONALE AND OBJECTIVES

To investigate the implication of a Magnetic resonance imaging (MRI) risk stratification system on the selection of patients with locally advanced rectal cancer (LARC) who can benefit from adjuvant chemotherapy (ACT) after neoadjuvant chemoradiotherapy (NCRT).

MATERIALS AND METHODS

This retrospective study included 328 patients with LARC who underwent NCRT and surgery. The median follow-up duration was 79 months (Interquartile range, 66-94 months). Cox logistic regression analysis was used to identify MRI risk factors and develop a risk stratification system to stratify patients into groups with high and low risks. Kaplan-Meier curves of distant metastasis-free survival (DMFS) and overall survival (OS) were used to show the benefits of ACT and stratify results based on the MRI risk stratification system and postoperative pathological staging.

RESULTS

An MRI risk stratification system was built based on four MRI risk factors, including MRI-identified T3b-T4 stage, N1-N2 stage, extramural venous invasion, and tumor deposits. 74 (22.6%) patients with 3-4 MRI risk factors were classified into the MRI high-risk group. ACT could significantly improve 5-year DMFS (19.2% versus 52.1%; p < 0.001) and OS (34.6% versus 75.0%; p < 0.001) for patients in the MRI high-risk group, while ACT had no survival benefit for patients in the MRI low-risk group. The benefits of ACT were not observed in patients with any pathological staging subgroups (ypT0-2N0, ypT3-4N0, and ypN+).

CONCLUSION

Patients in the MRI high-risk group could benefit from ACT, regardless of postoperative pathological staging. Baseline MRI should be considered more in ACT decision-making.

Can patients with good tumor regression grading after neoadjuvant chemoradiotherapy be exempted from lateral lymph node dissection?

OBJECTIVE

To investigate whether lateral lymph node (LLN) dissection (LLND) can be exempted in patients with good tumor regression grading (TRG) after neoadjuvant chemoradiotherapy (nCRT)?

METHODS

A retrospective study was conducted on consecutive patients with advanced rectal cancer who underwent nCRT and total mesorectal resection plus selective LLND at our institution. The primary outcomes are the relationship between LLN metastasis (LLNM) and magnetic resonance imaging TRG (mrTRG) and the relationship between LLNM and pathological TRG (pTRG).

RESULTS

A total of 91 patients were included, of which 24 patients (26.4%) had LLNM, 67 patients (73.6%) had no LLNM. There were significant differences of the maximum short-axis of LLN before and after nCRT, short-axis reduction rate of the LLN with maximum short-axis, length diameter reduction rate of primary tumor, mrTRG, and pTRG between the two groups. Multivariate logistic regression showed that mrTRG (P = 0.026) and pTRG (P = 0.013) were independent predictors for LLNM. The combination used by mrTRG and the maximum short-axis of LLNs ≥ 8 mm before nCRT and the maximum short-axis of LLN ≥ 5 mm after nCRT achieved specificity of 0.970, positive predictive value (PPV) of 0.867, and negative predictive value (NPV) of 0.855. The same combination used by pTRG achieved the specificity of 0.970, PPV of 0.857 and NPV of 0.844.

CONCLUSION

The suspected positive LLNs tend to be sterilized by nCRT in patients who have a very good response to nCRT. It is rational to avoid LLND in patients whose primary tumor and LLNs both show good response to nCRT.

Lymph node yield less than 12 is not a poor predictor of survival in locally advanced rectal cancer after laparoscopic TME following neoadjuvant chemoradiotherapy

Purpose

Previous studies have confirmed that neoadjuvant chemoradiotherapy (nCRT) may reduce the number of lymph nodes retrieved in rectal cancer. However, it is still controversial whether it is necessary to harvest at least 12 lymph nodes for locally advanced rectal cancer (LARC) patients who underwent nCRT regardless of open or laparoscopic surgery. This study was designed to evaluate the relationship between lymph node yield (LNY) and survival in LARC patients who underwent laparoscopic TME following nCRT.

Methods

Patients with LARC who underwent nCRT followed by laparoscopic TME were retrospectively analyzed. The relationship between LNY and survival of patients was evaluated, and the related factors affecting LNY were explored. To further eliminate the influence of imbalance of clinicopathological features on prognosis between groups, propensity score matching was conducted.

Results

A total of 257 consecutive patients were included in our study. The median number of LNY was 10 (7 to 13) in the total cohort. There were 98 (38.1%) patients with 12 or more lymph nodes harvested (LNY ≥12 group), and 159 (61.9%) patients with fewer than 12 lymph nodes retrieved (LNY <12 group). There was nearly no significant difference between the two groups in clinicopathologic characteristics and surgical outcomes except that the age of LNY <12 group was older (P<0.001), and LNY <12 group tended to have more TRG 0 cases (P<0.060). However, after matching, when 87 pairs of patients obtained, the clinicopathological features were almost balanced between the two groups. After a median follow-up of 65 (54 to 75) months, the 5-year OS was 83.9% for the LNY ≥12 group and 83.6% for the LNY <12 group (P=0.893), the 5-year DFS was 78.8% and 73.4%, respectively (P=0.621). Multivariate analysis showed that only patient age, TRG score and ypN stage were independent factors affecting the number of LNY (all P<0.05). However, no association was found between LNY and laparoscopic surgery-related factors.

Conclusions

For LARC patients who underwent nCRT followed by laparoscopic TME, the number of LNY less than 12 has not been proved to be an adverse predictor for long-term survival. There was no correlation between LNY and laparoscopic surgery-related factors.

Lymph node regression grading of locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy

Neoadjuvant chemoradiotherapy (nCRT) and total rectal mesenteric excision are the main standards of treatment for locally advanced rectal cancer (LARC). Lymph node regression grade (LRG) is an indicator of prognosis and response to preoperative nCRT based on postsurgical metastatic lymph node pathology. Common histopathological findings in metastatic lymph nodes after nCRT include necrosis, hemorrhage, nodular fibrosis, foamy histiocytes, cystic cell reactions, areas of hyalinosis, residual cancer cells, and pools of mucin. A number of LRG systems designed to classify the amount of lymph node regression after nCRT is mainly concerned with the relationship between residual cancer cells and regressive fibrosis and with estimating the number of lymph nodes existing with residual cancer cells. LRG offers significant prognostic information, and in most cases, LRG after nCRT correlates with patient outcomes. In this review, we describe the systematic classification of LRG after nCRT, patient prognosis, the correlation with tumor regression grade, and the typical histopathological findings of lymph nodes. This work may serve as a reference to help predict the clinical complete response and determine lymph node regression in patients based on preservation strategies, allowing for the formulation of more accurate treatment strategies for LARC patients, which has important clinical significance and scientific value.

Role of MRI‑based radiomics in locally advanced rectal cancer (Review)

Colorectal cancer is the third most common type of cancer, with high morbidity and mortality rates. In particular, locally advanced rectal cancer (LARC) is difficult to treat and has a high recurrence rate. Neoadjuvant chemoradiotherapy (NCRT) is one of the standard treatment programs of LARC. If the response to treatment and prognosis in patients with LARC can be predicted, it will guide clinical decision‑making. Radiomics is characterized by the extraction of high‑dimensional quantitative features from medical imaging data, followed by data analysis and model construction, which can be used for tumor diagnosis, staging, prediction of treatment response and prognosis. In recent years, a number of studies have assessed the role of radiomics in NCRT for LARC. MRI‑based radiomics provides valuable data and is expected to become an imaging biomarker for predicting treatment response and prognosis. The potential of radiomics to guide personalized medicine is widely recognized; however, current limitations and challenges prevent its application to clinical decision‑making. The present review summarizes the applications, limitations and prospects of MRI‑based radiomics in LARC.

Histopathological, Radiological, and Demographic Factors Predicting the Response to Neoadjuvant Therapy for Rectal Cancer

BACKGROUND/AIM

While the treatment for early stage rectal cancer is surgery, when a diagnosis is made at a locally advanced stage, it is recommended to start treatment with neoadjuvant chemoradiotherapy. Therefore, it is important to determine which patients will respond best to neoadjuvant treatment. The aim of this study was to investigate which hematological, histopathological, and radiological parameters can predict the response to chemoradiotherapy.

METHODS AND MATERIAL

A retrospective examination was made of 43 patients who underwent surgery following neoadjuvant chemoradiotherapy because of locally advanced stage rectal cancer. Demographic data were collected from the patient files, and the radiological, histopathological, and laboratory findings before neoadjuvant chemoradiotherapy were compared with the findings after treatment.

RESULTS

In the postoperative evaluation, a pathological complete response was determined in 25.50% of the patients. Lymphovascular invasion, perineural invasion, and absence of necrosisis were seen to be statistically related to major response (p < 0.05), and in patients where the tumor was closer than 6 cm to the anal verge, the response was better CONCLUSION: When the findings were examined, histopathological lymphovascular invasion, perineural invasion, the presence of necrosis, and the anal verge distance were evaluated as parameters predicting the response to neoadjuvant chemoradiotherapy in rectal cancer.