The importance of MRI for rectal cancer evaluation

Research progress in multimodal radiomics of rectal cancer tumors and peritumoral regions in MRI

Rectal cancer (RC) is one of the most common malignant tumors of the digestive system and has an alarmingly high incidence and mortality rate globally. Compared to conventional imaging examinations, radiomics can extract quantitative features that reflect tumor heterogeneity and mine data from medical images. In this review, we discuss the potential value of multimodal MRI-based radiomics in the diagnosis and treatment of RC, with a special emphasis on the role of peritumoral tissue characteristics in clinical decision-making. Existing studies have shown that a radiomics model integrating intratumoral and peritumoral characteristics has good application prospects in RC staging evaluation, efficacy prediction, metastasis monitoring, recurrence early warning, and prognosis judgment. At the same time, this paper also objectively analyzes the existing methodological limitations in this field, including insufficient data standardization, inadequate model validation, limited sample size and poor reproducibility of results. By combining existing evidence, this review aimed to enhance the attention of clinicians and radiologists on the characteristics of peritumoral tissues and promote the translational application of radiomics technology in the individualized treatment of RC.

Total neoadjuvant therapy for locally advanced rectal cancer

OBJECTIVES

This is a protocol for a Cochrane Review (intervention). The objectives are as follows: To assess the effectiveness and safety of total neoadjuvant therapy versus standard therapy in individuals with locally advanced rectal cancer.

T2-weighted imaging of rectal cancer using a 3D fast spin echo sequence with and without deep learning reconstruction: A reader study

PURPOSE

To compare image quality and clinical utility of a T2-weighted (T2W) 3-dimensional (3D) fast spin echo (FSE) sequence using deep learning reconstruction (DLR) versus conventional reconstruction for rectal magnetic resonance imaging (MRI).

METHODS

The study included 50 patients with rectal cancer who underwent rectal MRI consecutively between July 7, 2020 and January 20, 2021 using a T2W 3D FSE sequence with DLR and conventional reconstruction. Three radiologists reviewed the two sets of images, scoring overall SNR, motion artifacts, and overall image quality on a 3-point scale and indicating clinical preference for DLR or conventional reconstruction based on those three criteria as well as image characterization of bowel wall layer definition, tumor invasion of muscularis propria, residual disease, fibrosis, nodal margin, and extramural venous invasion.

RESULTS

Image quality was rated as moderate or good for both DLR and conventional reconstruction for most cases. DLR was preferred over conventional reconstruction in all of the categories except for bowel wall layer definition.

CONCLUSION

Both conventional reconstruction and DLR provide acceptable image quality for T2W 3D FSE imaging of rectal cancer. DLR was clinically preferred over conventional reconstruction in almost all categories.

Relationship between apparent diffusion coefficient values and clinicopathologic features in rectal cancer: a cross-sectional study

Background

The prognosis of rectal cancer is closely related to its clinicopathologic features. Accurate preoperative assessment of these features is crucial for treatment planning and prognosis prediction. The apparent diffusion coefficient (ADC), derived from diffusion-weighted imaging (DWI), has shown potential as a noninvasive imaging biomarker for evaluating tumor characteristics. This study aimed to explore the relationship between ADC values and the clinicopathological features of rectal cancer.

Methods

We retrospectively recruited 97 eligible patients with rectal adenocarcinoma who underwent magnetic resonance imaging (MRI) and surgical resection at our institution between January 2023 and December 2023. Each patient was evaluated for the presence of extramural vascular invasion (EMVI) or circumferential resection margin (CRM) on MRI, and the mean (ADCmean), minimum (ADCmin), and maximum (ADCmax) ADC values were calculated. Moreover, the relationship between the ADC values and clinicopathological features, including tumor stage, histologic grade, lymphovascular invasion, perineural invasion, and lymph node metastasis, were statistically analyzed.

Results

Among 97 patients with rectal cancer, the mean age was 61.40±10.46 years and 60 (61.9%) were males. ADCmean, ADCmin, and ADCmax were significantly lower in patients with EMVI or CRM than in those without EMVI or CRM (P<0.05). Pathologic T1-2 staging exhibited higher ADCmean (0.79±0.26 vs. 0.61±0.22, P=0.001), ADCmin (0.71±0.26 vs. 0.55±0.22, P=0.002) and ADCmax (0.89±0.26 vs. 0.75±0.22, P=0.004) compared with T3-4 staging. Highly and moderately differentiated tumors had higher ADCmean, ADCmin, and ADCmax than less-differentiated tumors (P<0.05). Patients with lymphovascular invasion, perineural invasion, and lymph node metastasis showed significantly lower ADCmean, ADCmin, and ADCmax than those without these conditions (P<0.05). ADCmean, ADCmin and ADCmax were negatively correlated with EMVI (r=-0.334, -0.340, -0.302), CRM (r=-0.362, -0.414, -0.276), pathologic T-stage (r=-0.324, -0.313, -0.276), histologic grade (r=-0.353, -0.352, -0.289), lymphovascular invasion (r=-0.405, -0.384, -0.421), perineural invasion (r=-0.428, -0.407, -0.265), and lymph node metastasis (r=-0.347, -0.316, -0.268) in rectal cancer.

Conclusions

ADC values were negatively associated with different clinicopathological features of rectal cancer, suggesting their potential role as noninvasive imaging markers for preoperative tumor assessment.

Management of the Malignant Rectal Polyp-A Narrative Review

PURPOSE

The aim of this review is to provide a contemporary update on the current management approaches and options with specific considerations in malignant rectal polyps.

METHODS

A literature review was carried out in PubMed, Embase and Cochrane databases using the keywords "malignant" and "polyp*". Only publications in English language were included.

RESULTS

Histopathological features including margins, depth of invasion, tumour grade, LVI and tumour budding determines the risk of lymph node metastasis in malignant polyps. Rectal malignant polyps should be considered differently compared to their colonic counterpart. A low threshold should be considered for utilising transrectal excision to fully excise the polyp and to assess the margins. The rates of complete pathological response associated with total neoadjuvant therapy as well as the advent of "watch and wait" adds to the complexity of managing malignant rectal polyps.

CONCLUSIONS

The management of malignant colorectal polyps lies in risk-stratifying patients who will benefit from an oncological resection.

Gastrointestinal tumor personalized immunotherapy: an integrated analysis from molecular genetics to imaging biomarkers

The immunotherapy landscape for gastrointestinal (GI) tumors is rapidly evolving. There is an urgent need for reliable biomarkers capable of predicting treatment outcomes to optimize therapeutic strategies and enhance patient prognosis. This review presents a comprehensive overview of biomarkers associated with the immunotherapy response of GI tumors, covering advances in molecular genetics, histopathological markers, and imaging. Key molecular biomarkers, such as microsatellite instability, tumor mutational burden, and programmed death-ligand 1 expression, remain critical for identifying patients likely to benefit from immune checkpoint inhibitors. The significance of tumor-infiltrating lymphocytes, notably the CD8+ T cell to regulatory T cell ratio, as a predictor of immunotherapy response is explored. In addition, advanced imaging techniques, including computed tomography (CT), magnetic resonance imaging, and positron emission tomography-CT, facilitate the noninvasive evaluation of tumor biology and therapeutic response. By bridging molecular and imaging data, this integrated strategy enhances precision in patient selection, treatment monitoring, and adaptive therapy design. Future studies should aim to validate these biomarkers in larger, multicenter cohorts and focus on clinical translation to advance precision medicine in GI oncology.

Diagnostic performance of node-RADS classification for primary lymph node assessment in rectal cancer: a modality benchmarking study

PURPOSE

To evaluate how well the Node Reporting and Data System (Node-RADS) diagnoses lymph node involvement (LNI) in the initial stages of rectal cancer, utilizing contrast-enhanced CT (CE-CT), T2-weighted MRI (T2WI) and contrast-enhanced T1-weighted MRI (T1CE).

METHODS

This retrospective study included 113 rectal cancer patients who underwent radical surgery without neoadjuvant therapy. Two radiologists independently assessed regional lymph nodes using the highest NODE-RADS classification and histopathology as reference criteria. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Statistical analysis was performed using the McNemar test with Bonferroni correction for multiple comparisons.

RESULTS

Node-RADS showed improved diagnostic performance over short-axis diameter (SAD) in all modalities (AUC: 0.838 vs. 0.744 for CE-CT, 0.845 vs. 0.747 for T2WI, 0.853 vs. 0.786 for T1CE; all P < 0.05). The sensitivity and specificity of Node-RADS across three modalities ranged from 76.19 - 78.57% and 91.55 - 92.96%, respectively. Pairwise comparisons of sensitivity and specificity among the three modalities showed no significant differences after Bonferroni correction (all McNemar test P = 1.0). There was no significant difference in Node-RADS performance among the three modalities (all P > 0.05). The weighted kappa values were 0.742-0.798.

CONCLUSION

Node-RADS demonstrated superior diagnostic performance over SAD measurements and similar diagnostic effectiveness in assessing LNI for primary rectal cancer stages across CE-CT, T2WI, and T1CE.

Extramural venous invasion in gastric cancer: 9.4T magnetic resonance imaging assessment and circular RNA functional analysis

BACKGROUND

Extramural venous invasion (EMVI) is a critical prognostic factor in gastric cancer (GC); however, its detection and underlying molecular mechanisms remain underexplored.

AIM

To investigate the relationship between EMVI and expression of the circular RNA hsa_circ_0097977 in orthotopic GC mouse models.

METHODS

A retrospective analysis was conducted in addition to a preclinical animal study, involving 13 GC patients and 24 orthotopic GC mouse models, respectively. EMVI was assessed using axial T2-weighted fat suppression sequences on a 9.4T magnetic resonance imaging (MRI) with histopathological confirmation as the gold standard for EMVI. The impact of hsa_circ_0097977 on EMVI and GC cell function was evaluated. Statistical analyses comprised consistency, area under the curve analysis, correlation, χ 2/Fisher exact, and Mann-Whitney U/t-tests, with significance set at P < 0.05.

RESULTS

EMVI was accurately detected using 9.4T MRI in orthotopic mouse models with an area under the curve of 0.843 (sensitivity 78.6%, specificity 90.0%). MRI detected EMVI was the only imaging factor associated with distant metastasis (P = 0.04). Furthermore, knockdown of hsa_circ_0097977 was the only factor associated with EMVI (P = 0.043, 0.038) and led to reduced invasion and increased apoptosis in GC cells.

CONCLUSION

EMVI, a risk factor for distant metastasis in GC, is detectable by 9.4T MRI and regulated by hsa_circ_0097977, making it a potential therapeutic target.

Radiomic Features of Mesorectal Fat as Indicators of Response in Rectal Cancer Patients Undergoing Neoadjuvant Therapy

BACKGROUND

Rectal cancer represents a major cause of mortality in the United States. Management strategies are highly individualized, depending on patient-specific factors and tumor characteristics. The therapeutic landscape is rapidly evolving, with notable advancements in response rates to both radiotherapy and chemotherapy. For locally advanced rectal cancer (LARC, defined as up to T3-4 N+), the standard of care involves total mesorectal excision (TME) following neoadjuvant chemoradiotherapy (nCRT). Magnetic resonance imaging (MRI) has emerged as the gold standard for local tumor staging and is increasingly pivotal in post-treatment restaging.

AIM

In our study, we proposed an MRI-based radiomic model to identify characteristic features of peritumoral mesorectal fat in two patient groups: good responders and poor responders to neoadjuvant therapy. The aim was to assess the potential presence of predictive factors for favorable or unfavorable responses to neoadjuvant chemoradiotherapy, thereby optimizing treatment management and improving personalized clinical decision-making.

METHODS

We conducted a retrospective analysis of adult patients with LARC who underwent pre- and post-nCRT MRI scans. Patients were classified as good responders (Group 0) or poor responders (Group 1) based on MRI findings, including tumor volume reduction, signal intensity changes on T2-weighted and diffusion-weighted imaging (DWI), and alterations in the circumferential resection margin (CRM) and extramural vascular invasion (EMVI) status. Classification criteria were based on the established literature to ensure consistency. Key clinical and imaging parameters, such as age, TNM stage, CRM involvement, and EMVI presence, were recorded. A radiomic model was developed using the LASSO algorithm for feature selection and regularization from 107 extracted radiomic features.

RESULTS

We included 44 patients (26 males and 18 females) who, following nCRT, were categorized into Group 0 (28 patients) and Group 1 (16 patients). The pre-treatment MRI analysis identified significant features (out of 107) for each sequence based on the Mann-Whitney test and t-test. The LASSO algorithm selected three features (shape_Sphericity, shape_Maximum2DDiameterSlice, and glcm_Imc2) for the construction of the radiomic logistic regression model, and ROC curves were subsequently generated for each model (AUC: 0.76).

CONCLUSIONS

We developed an MRI-based radiomic model capable of differentiating and predicting between two groups of rectal cancer patients: responders and non-responders to neoadjuvant chemoradiotherapy (nCRT). This model has the potential to identify, at an early stage, lesions with a high likelihood of requiring surgery and those that could potentially be managed with medical treatment alone.

Shared Decision Making in the Treatment of Rectal Cancer

Background/Objectives: The management of locally advanced rectal cancer has evolved significantly, shaped by advances in multimodal neoadjuvant therapy and a growing emphasis on organ preservation through the watch-and-wait approach. These advancements, however, introduce complex treatment decisions that require careful consideration by both patients and clinicians. Methods: This narrative review explores the evolution of the management of locally advanced rectal cancer and the role of shared decision-making in guiding treatment decisions, particularly for patients facing decisions between surgical resection and watch-and-wait. Additionally, it discusses the development of tools to aid in shared-decision making, current challenges in implementing shared decision-making and future directions for improvement patient centered care in locally advanced rectal cancer management. Results: Considerations for decision making include anatomical considerations that influence surgical options, the potential benefits and risks of watch-and-wait versus surgical resection of the rectum, and the impact of treatment on bowel, urinary, and sexual function. Additionally, patients must weigh the long-term implications of their choices on quality of life. Conclusions: Shared decision-making has emerged as a critical component of patient-centered care and ensures that treatment decisions align with patients' values and priorities. Given the preference-sensitive nature of the management of locally advanced rectal cancer, shared decision-making plays an important role in helping patients navigate these decisions.

From Diversion to Permanence: Trends in Ostomy Creation in Rectal Cancer Surgery

Rectal cancer surgery has undergone transformative advancements over the past few decades, evolving from radical, high-morbidity procedures to more refined techniques focused on both oncological outcomes and the preservation of anorectal function. This review provides a brief overview of the history of rectal cancer surgery, highlighting key innovations in imaging, neoadjuvant therapy, and minimally invasive techniques that have significantly reduced the need for permanent and temporary ostomies. Additionally, the current indications for both permanent and temporary ostomies are reviewed, including a discussion of associated complications, such as non-reversal, parastomal hernias, stomal prolapse, stenosis, and skin-related issues, along with strategies and techniques to mitigate these complications. This review underscores the importance of ongoing innovation and individualized surgical planning to enhance patient outcomes in rectal cancer care by understanding the historical context, contemporary practices, and associated challenges.

Rising incidence trends of synchronous prostate and rectal cancers: a population-based study

BACKGROUND

There is a lack of comprehensive reports on time trends in synchronous prostate and rectal cancers. To address this, we conducted the largest cohort study to date to assess these trends in a population-based setting.

METHODS

We included all adult (ages 18-99) men with incident prostate cancer in the Swedish Cancer Register in 1993-2019. Age-standardized incidence rates (ASIRs) of prostate cancer per 100,000 male population per year were calculated and compared to the ASIR of synchronous (± 6 months from rectal cancer diagnosis) prostate cancer. Age-adjusted synchronous-to-general incidence rate ratios (IRRs) were predicted using Poisson regression. As a sensitivity analysis to assess the effect of incidental findings due to the anatomical proximity, we investigated synchronous prostate and non-sigmoid colon cancers.

RESULTS

Among 238,252 prostate cancer cases, 594 were synchronous with rectal cancer. The incidence of synchronous prostate cancer increased over the study period, with mean ASIR rising from 418/100,000 (1993-2001) to 788/100,000 (year 2011-2019). The synchronous-to-general IRR increased from 1.92 (95% confidence interval (CI) 1.60-2.31) to 2.61 (95% CI 2.32-2.95) over the same periods. Prostate cancer was also more commonly diagnosed in conjunction with non-sigmoid colon cancer than in the overall male population, but no time trend was observed.

INTERPRETATION

The incidence of synchronous prostate and rectal cancers has increased over the past 20 years in Sweden, with no signs of plateauing. Future studies are warranted to explore factors contributing to prostate cancer overdiagnosis and to optimize clinical management strategies for this complex patient group.

Application of TransUnet Deep Learning Model for Automatic Segmentation of Cervical Cancer in Small-Field T2WI Images

Effective segmentation of cervical cancer tissue from magnetic resonance (MR) images is crucial for automatic detection, staging, and treatment planning of cervical cancer. This study develops an innovative deep learning model to enhance the automatic segmentation of cervical cancer lesions. We obtained 4063 T2WI small-field sagittal, coronal, and oblique axial images from 222 patients with pathologically confirmed cervical cancer. Using this dataset, we employed a convolutional neural network (CNN) along with TransUnet models for segmentation training and evaluation of cervical cancer tissues. In this approach, CNNs are leveraged to extract local information from MR images, whereas Transformers capture long-range dependencies related to shape and structural information, which are critical for precise segmentation. Furthermore, we developed three distinct segmentation models based on coronal, axial, and sagittal T2WI within a small field of view using multidirectional MRI techniques. The dice similarity coefficient (DSC) and mean Hausdorff distance (AHD) were used to assess the performance of the models in terms of segmentation accuracy. The average DSC and AHD values obtained using the TransUnet model were 0.7628 and 0.8687, respectively, surpassing those obtained using the U-Net model by margins of 0.0033 and 0.3479, respectively. The proposed TransUnet segmentation model significantly enhances the accuracy of cervical cancer tissue delineation compared to alternative models, demonstrating superior performance in overall segmentation efficacy. This methodology can improve clinical diagnostic efficiency as an automated image analysis tool tailored for cervical cancer diagnosis.

Comparison of prognosis for T4b rectal cancer with different pelvic compartment involvement treated using neoadjuvant chemoradiotherapy and implications for refinement of the current T staging system: A retrospective cohort study

PURPOSE

Although classified as one stage, T4b rectal cancer actually represents a group of heterogeneous diseases. Our study aimed to assess the prognosis difference of T4b rectal cancer involving inferior pelvic and other pelvic compartments. This information may be helpful in refinement of the current T staging system.

METHODS

We retrospectively analysed data from 195 patients with magnetic resonance imaging-identified locally advanced T4b rectal cancer who received neoadjuvant chemoradiotherapy between January 2010 and December 2019. 104 patients had only inferior pelvic compartment involvement (group A) while 91 patients had anterior, posterior or lateral pelvic compartment involvement (group B). Short-term and long-term outcomes were compared between the two groups.

RESULTS

After neoadjuvant therapy, 80.8 % patients (84/104) in group A and 92.3 % patients (84/91) in group B underwent surgery. The R0 resection rates were 97.6 % and 89.3 %, respectively. 8.7 % patients (9/104) in group A achieved clinical complete response and adopted watch-and-wait strategy. Patients in group A had significantly superior 5-year progression-free survival (PFS) (67.8 % vs. 55.5 %, P = 0.032) and overall survival (OS) (89.6 % vs. 71.8 %, P = 0.001) than group B. Multivariable Cox regression analysis also identified pelvic compartment involvement classification as an independent predictor of PFS (hazard ratio 1.776, P = 0.046) and OS (hazard ratio 3.477, P = 0.004).

CONCLUSION

T4b rectal cancers with involvement limited to the inferior pelvic compartment had superior prognosis compared to those involving other pelvic compartments. These differences should be investigated further and taken into consideration in refinement of the current T staging system.

The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of colorectal cancer, 2024 update

The 2024 updates of the Chinese Society of Clinical Oncology (CSCO) Clinical Guidelines for the diagnosis and treatment of colorectal cancer emphasize standardizing cancer treatment in China, highlighting the latest advancements in evidence-based medicine, healthcare resource access, and precision medicine in oncology. These updates address disparities in epidemiological trends, clinicopathological characteristics, tumor biology, treatment approaches, and drug selection for colorectal cancer patients across diverse regions and backgrounds. Key revisions include adjustments to evidence levels for intensive treatment strategies, updates to regimens for deficient mismatch repair (dMMR)/ microsatellite instability-high (MSI-H) patients, proficient mismatch repair (pMMR)/ microsatellite stability (MSS) patients who have failed standard therapies, and rectal cancer patients with low recurrence risk. Additionally, recommendations for digital rectal examination and DNA polymerase epsilon (POLE)/ DNA polymerase delta 1 (POLD1) gene mutation testing have been strengthened. The 2024 CSCO Guidelines are based on both Chinese and international clinical research, as well as expert consensus, ensuring their relevance and applicability in clinical practice, while maintaining a commitment to scientific rigor, impartiality, and timely updates.

Comparing efficacy and safety of transanal vs. laparoscopic total mesorectal excision for middle and low rectal cancer: Updated meta-analysis

OBJECTIVE

This study aimed to compare the efficacy and safety of transanal total mesorectal excision (TaTME) with laparoscopic total mesorectal excision (LaTME) in patients with middle and low rectal cancer.

METHODS

A comprehensive search of PubMed, Embase, and Cochrane databases was conducted to identify studies evaluating TaTME and LaTME from inception to June 2023. An additional search update was conducted in November 2024 to capture recently published studies. A total of 24 studies (3 randomized controlled trials and 21 observational studies) involving 3443 patients were included. Meta-analysis assessed key outcomes, including circumferential resection margin (CRM) positivity, R0 resection rate, completeness of mesorectal excision, conversion to open surgery, and postoperative complications.

RESULTS

TaTME was associated with a significantly lower positive rate of CRM (odds ratio [OR] = 0.68, 95 % confidence interval [CI] = 0.49-0.94), a higher R0 resection rate (OR = 1.74, 95 % CI = 1.17-2.59), and a reduced incidence of conversion to open surgery (OR = 0.16, 95 % CI = 0.10-0.26) compared to LaTME. Completeness of ME was comparable between the two groups (OR = 1.29, 95 % CI = 0.85-1.96). There was no significant difference in postoperative complications (OR = 0.80, 95 % CI = 0.62-1.03) or 30-day mortality (OR = 0.42, 95 % CI = 0.12-1.47).

CONCLUSIONS

TaTME demonstrates superior outcomes in terms of CRM positivity, R0 resection, and conversion rates compared to LaTME, with comparable safety profiles and no significant differences in postoperative complications or 30-day mortality. These findings support TaTME as a viable surgical approach for middle and low rectal cancer.

Multiparametric MRI-Based Deep Learning Models for Preoperative Prediction of Tumor Deposits in Rectal Cancer and Prognostic Outcome

RATIONALE AND OBJECTIVES

To investigate the predictive value of a deep learning model based on multiparametric MRI (mpMRI) for tumor deposit (TD) in rectal cancer (RC) patients and to analyze their prognosis.

MATERIALS AND METHODS

Data from 529 RC patients who underwent radical surgery at two centers were retrospectively collected. 379 patients from center one were randomly divided into a training set (n = 265) and an internal validation (invad) set (n = 114) in a 7:3 ratio. 150 patients from center two were included in the external validation (exvad) set. Univariate and multivariate analyses were performed to identify independent clinical predictors and to construct a clinical model. Preoperative mpMRI images were utilized to extract deep features through the ResNet-101 model. Following feature selection, a deep learning model was developed. A nomogram was created by combining the clinical model with the deep learning model. The clinical applicability of each model was assessed using ROC curves, decision curve analysis (DCA), clinical impact curves (CIC), and deLong test. Kaplan-Meier survival analysis was conducted to evaluate prognostic outcome among patients.

RESULTS

Among the 529 patients, 142 (26.8%) were TD positive. In the training set, clinical model was constructed based on clinical independent predictors (cT and cN). 30 deep features were selected to calculate the deep learning radscore (DLRS) and develop the deep learning (DL) model. The AUC values for the clinical model were 0.724, 0.836, and 0.763 in the training set, invad set, and exvad set, respectively. The AUC values for the DL model were 0.903, 0.853, and 0.874, respectively. The nomogram achieved higher AUC values of 0.925, 0.919, and 0.9, respectively. The DeLong test indicated that the predictive performance of the nomogram was superior to both the DL model and the clinical model in training and invad sets. Kaplan-Meier survival analysis showed that both the DL model and the nomogram effectively stratified patients into high-risk and low-risk groups for 3-year DFS (p < 0.05).

CONCLUSION

The nomogram, which integrates mpMRI-based deep radiomic features and clinical characteristics, effectively predicts preoperative TD status in RC. Both the DL model and the nomogram can effectively stratify patients' 3-year DFS risk.

Development and evaluation of the mrTE scoring system for MRI-detected tumor deposits and extramural venous invasion in rectal cancer

PURPOSE

Tumor deposits (TDs) and extramural venous invasion (EMVI) in locally advanced rectal cancer (LARC) are MRI-detectable markers that reflect the invasive and metastatic potential of tumors. However, both mrTDs and mrEMVI are closely associated with peritumoral vascular signals, and they show a high degree of statistical correlation. We developed a novel scoring system that integrates mrTDs and mrEMVI into a single parameter, simplifying the assessment process and capturing the prognostic value of both factors simultaneously.

METHODS

We retrospectively included LARC patients who received neoadjuvant chemoradiotherapy at five centers and proposed a novel MRI-based scoring system, mrTE (derived from mrTDs and mrEMVI), to integrate the prognostic significance of mrEMVI and mrTDs in rectal cancer. The prognostic value of different mrTE scores was evaluated using Kaplan-Meier curves and the Cox model. The predictive accuracy of the new scoring system was evaluated using the integrated area under the ROC curve (iAUC).

RESULTS

A total of 1188 patients with LARC were included in the evaluation cohort to assess the reliability of the novel imaging scoring system. Based on the mrTE scores ranging from 0 to 2, the patients were categorized into three groups. The 3-year disease-free survival rates for the groups were 88.1%, 78.1%, and 51.9% (score 1 vs 0: HR 2.00, 95% CI 1.36-2.93, p < 0.001; score 2 vs 0: HR 4.75, 95% CI 3.61-6.26, p < 0.001). The mrTE scoring system demonstrated superior performance in predicting DFS compared to other clinical and imaging markers, with a higher predictive accuracy (iAUC = 0.707).

CONCLUSIONS

The mrTE scoring system simplifies the clinical assessment of relevant MR markers and has proven to be an effective tool for predicting the prognosis of LARC patients.

Personalized medicine in colorectal cancer: a comprehensive study of precision diagnosis and treatment

Colorectal cancer is a common and fatal disease that affects many people globally. CRC is classified as the third most prevalent cancer among males and the second most frequent cancer among females worldwide. The purpose of this article is to examine how personalized medicine might be used to treat colorectal cancer. The classification of colorectal cancer based on molecular profiling, including the detection of significant gene mutations, genomic instability, and gene dysregulation, is the main topic of this discussion. Advanced technologies and biomarkers are among the detection methods that are explored, demonstrating their potential for early diagnosis and precise prognosis. In addition, the essay explores the world of treatment possibilities by providing light on FDA-approved personalized medicine solutions that provide individualized and precise interventions based on patient characteristics. This article assesses targeted treatments like cetuximab and nivolumab, looks at the therapeutic usefulness of biomarkers like microsatellite instability (MSI) and circulating tumor DNA (ctDNA), and investigates new approaches to combat resistance. Through this, our review provides a thorough overview of personalized medicine in the context of colorectal cancer, ultimately highlighting its potential to revolutionize the field and improve patient care.

Mastering rectal cancer MRI: From foundational concepts to optimal staging

MRI plays a critical role in the local staging, restaging, surveillance, and risk stratification of patients, ensuring they receive the most tailored therapy. As such, radiologists must be familiar not only with the key MRI findings that influence management decisions but also with the appropriate MRI protocols and structured reporting. Given the complexity of selecting the optimal therapy for each patient-which often requires multidisciplinary discussions-radiologists should be well-versed in relevant treatment strategies and surgical terms, understanding their significance in guiding patient care. In this manuscript, we review the most common treatment options for managing patients with rectal adenocarcinoma, emphasizing key MRI principles and protocol characteristics for accurate staging. We also highlight important anatomical landmarks and essential factors to be described during baseline assessment. Additionally, we discuss crucial information for restaging and surveillance.

A novel MRI-based radiomics for preoperative prediction of lymphovascular invasion in rectal cancer

BACKGROUND

To develop and validate a clinical-radiomics model for preoperative prediction of lymphovascular invasion (LVI) in rectal cancer.

METHODS

This retrospective study included data from 239 patients with pathologically confirmed rectal adenocarcinoma from two centers, all of whom underwent MRI examinations. Cases from the first center (n = 189) were randomly divided into a training set and an internal validation set at a 7:3 ratio, while cases from the second center (n = 50) constituted the external validation set. The clinical features and MRI imaging characteristics of the patients in the training set were analyzed. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for LVI in rectal cancer, and these risk factors were then used to construct a clinical model. Regions of interest (ROIs) were delineated on T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) sequences for feature extraction. After feature reduction and selection, the most strongly correlated features were identified, and their respective regression coefficients were calculated to construct the radiomics model. Finally, a combined clinical-radiomics model was built using a weighted linear combination of features and was visualized as a nomogram. The predictive performance of each model was quantified using receiver operating characteristics (ROC) curves and the area under the curve (AUC) in both training and validation sets, with DeLong analysis being used to compare model performance. Decision curve analysis (DCA) was used to evaluate the clinical utility of each model in the validation sets.

RESULTS

In the 239 patients, the combined model outperformed the clinical and radiomics models in predicting LVI in rectal cancer. The combined model showed excellent predictive performance in the training, internal validation, and external validation sets, with AUCs of 0.90 (0.88-0.97), 0.88 (0.78-0.99), and 0.88 (0.78-0.95), respectively. The sensitivity values were 75.9%, 68.8%, and 80.0%, respectively, and the specificity values were 90.3%, 92.7%, and 88.6%. DCA results indicated that the nomogram of the combined model had superior clinical utility compared with the clinical and radiomics models.

CONCLUSIONS

The clinical-radiomics nomogram serves as a valuable tool for non-invasive preoperative prediction of LVI status in patients with rectal cancer.

Unraveling the complexities of colorectal cancer and its promising therapies - An updated review

Colorectal cancer (CRC) continues to be a global health concern, necessitating further research into its complex biology and innovative treatment approaches. The etiology, pathogenesis, diagnosis, and treatment of colorectal cancer are summarized in this thorough review along with recent developments. The multifactorial nature of colorectal cancer is examined, including genetic predispositions, environmental factors, and lifestyle decisions. The focus is on deciphering the complex interactions between signaling pathways such as Wnt/β-catenin, MAPK, TGF-β as well as PI3K/AKT that participate in the onset, growth, and metastasis of CRC. There is a discussion of various diagnostic modalities that span from traditional colonoscopy to sophisticated molecular techniques like liquid biopsy and radiomics, emphasizing their functions in early identification, prognostication, and treatment stratification. The potential of artificial intelligence as well as machine learning algorithms in improving accuracy as well as efficiency in colorectal cancer diagnosis and management is also explored. Regarding therapy, the review provides a thorough overview of well-known treatments like radiation, chemotherapy, and surgery as well as delves into the newly-emerging areas of targeted therapies as well as immunotherapies. Immune checkpoint inhibitors as well as other molecularly targeted treatments, such as anti-epidermal growth factor receptor (anti-EGFR) as well as anti-vascular endothelial growth factor (anti-VEGF) monoclonal antibodies, show promise in improving the prognosis of colorectal cancer patients, in particular, those suffering from metastatic disease. This review focuses on giving readers a thorough understanding of colorectal cancer by considering its complexities, the present status of treatment, and potential future paths for therapeutic interventions. Through unraveling the intricate web of this disease, we can develop a more tailored and effective approach to treating CRC.

Short-term surgical outcomes of rectal adenocarcinoma surgical treatment in Latin America: a multicenter, retrospective assessment in 49 centers from 12 countries

INTRODUCTION

Rectal cancer is a prevalent disease that requires multidisciplinary management. Results of treatment of patients suffering from this malignancy in Latin America have been scarcely reported before.

METHODS

A retrospective, multicenter study was conducted to report preoperative and operative characteristics of patients intervened for rectal cancer in centers from Latin America during 2015-2022, and the short-term results of treatment were analyzed. The study was open to any center receiving rectal cancer patients, irrespective of volume. The main study outcome was 30-day postoperative complications including any deviation from the normal postoperative course (Clavien Dindo I to V).

RESULTS

A total of 2044 patients from 49 centers in 12 Latin American countries were included, with a mean age of 63 years. Twenty-five percent of patients were operated in low-volume centers. Twenty-nine percent of patients had a tumor located in the low rectum, and only 53% of patients had preoperative MRI for local staging. A total of 1052 patients (52%) received neoadjuvant therapy before surgery. Eighty-six percent of patients were operated by a specialized colorectal surgeon, and 31% of patients were intervened using a conventional approach. A total of 29.9% of patients presented a postoperative complication. The anastomotic leak rate was 8.9%. Fifty-eight percent of pathology reports had less than 12 lymph nodes harvested, and 22.9% of reports did not include mesorectal quality. In the multivariate analysis, neoadjuvant therapy (OR: 1.44, p-value: 0.023), urgent procedures (OR: 3.73, p-value: 0.049), intraoperative complications (OR: 2.21, p-value: 0.046), advanced tumors (OR: 1.39, p-value: 0.036), and prolonged surgery (OR: 1.74, p-value: 0.004) were found to be independently related to suffering postoperative complications.

CONCLUSIONS

This study includes information about the approach and results of rectal cancer management in Latin America at a large scale. In the future, this information can be used as a bridge to identify areas of improvement among rectal cancer patients' treatment in the region.

Nonoperative management of rectal cancer

The management of locally advanced rectal cancer has changed drastically in the last few decades due to improved surgical techniques, development of multimodal treatment approaches and the introduction of a watch and wait (WW) strategy. For patients with a complete response to neoadjuvant treatment, WW offers an opportunity to avoid the morbidity associated with total mesorectal excision in favor of organ preservation. Despite growing interest in WW, prospective data on the safety and efficacy of nonoperative management are limited. Challenges remain in optimizing multimodal treatment regimens to maximize tumor regression and in improving the accuracy of patient selection for WW. This review summarizes the history of treatment for rectal cancer and the development of a WW strategy. It also provides an overview of clinical considerations for patients interested in nonoperative management, including restaging strategies, WW selection criteria, surveillance protocols and long-term oncologic outcomes.

Rectal Cancer: Exploring Predictive Biomarkers Through Molecular Pathways Involved in Carcinogenesis

In 2022, colorectal cancer (CCR) had the second-highest incidence in Europe, preceded only by breast cancer [...].

Landscape of Biomarkers and Pathologic Response in Rectal Cancer: Where We Stand?

Colorectal cancer (CRC) is a neoplasm with a high prevalence worldwide, with a multimodal treatment that includes a combination of chemotherapy, radiotherapy, and surgery in locally advanced stages with acceptable pathological complete response (pCR) rates, this has improved with the introduction of total neoadjuvant therapy (TNT) reaching pCR rates up to 37% in compare with classic neoadjuvant treatment (NAT) where pCR rates of around 20-25% are achieved. However, the patient population that benefits most from this therapy has not been determined, and there is a lack of biomarkers that can predict the course of the disease. Multiple biomarkers have been studied, ranging from hematological and molecular markers by imaging technique and combinations of them, with contradictory results that prevent their use in routine clinical practice. In this review, we evaluate the most robust prognostic biomarkers to be used in clinical practice, highlighting their advantages and disadvantages and emphasizing biomarker combinations and their predictive value.

Role of Artificial Intelligence in MRI-Based Rectal Cancer Staging: A Systematic Review

Several studies explored the application of artificial intelligence (AI) in magnetic resonance imaging (MRI)-based rectal cancer (RC) staging, but a comprehensive evaluation remains lacking. This systematic review aims to review the performance of AI models in MRI-based RC staging. PubMed and Embase were searched from the inception of the database till October 2024 without any language and year restrictions. The prospective or retrospective studies evaluating AI models (including machine learning (ML) and deep learning (DL)) for diagnostic performance in MRI-based RC staging compared with any comparator were included in this review. The performance metrics were considered as outcomes. Two independent reviewers were involved in the study selection and data extraction to limit bias; any disagreements were resolved through mutual consensus or discussion with a third reviewer. A total of 716 records were identified from the databases. Out of these, 14 studies (1.95%) were finally included in this review. These studies were published between 2019 and 2024. Various MRI technologies were adapted by the studies and multiple AI models were developed. DL was the most common. The MRI images including T1-weighted images (14.28%), T2-weighted images (85.71%), diffusion-weighted images (42.85%), or the combination of these from different landscapes and systems were used to develop the AI models. The models were built using various techniques, mainly DL such as conventional neural network (28.57%), DL reconstruction (14.28%), Weakly supervISed model DevelOpment fraMework (7.12%), deep neural network (7.12%), Faster region-based CNN (7.12%), ResNet, DL-based clinical-radiomics nomogram (7.12%), LASSO (7.12%), and random forest classifier (7.12%). All the models that used single-type images or combined imaging modalities showed a better performance than manual assessment in terms of higher accuracy, sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and area under the curve with a score of >0.75. This is considered to be a good performance. The current study indicates that MRI-based AI models for RC staging show great promise with a high performance.

RPDNet: A reconstruction-regularized parallel decoders network for rectal tumor and rectum co-segmentation

Accurate segmentation of rectal cancer tumor and rectum in magnetic resonance imaging (MRI) is significant for tumor precise diagnosis and treatment plans determination. Variable shapes and unclear boundaries of rectal tumors make this task particularly challenging. Only a few studies have explored deep learning networks in rectal tumor segmentation, which mainly adopt the classical encoder-decoder structure. The frequent downsampling operations during feature extraction result in the loss of detailed information, limiting the network's ability to precisely capture the shape and boundary of rectal tumors. This paper proposes a Reconstruction-regularized Parallel Decoder network (RPDNet) to address the problem of information loss and obtain accurate co-segmentation results of both rectal tumor and rectum. RPDNet initially establishes a shared encoder and parallel decoders framework to fully utilize the common knowledge between two segmentation labels while reducing the number of network parameters. An auxiliary reconstruction branch is subsequently introduced by calculating the consistency loss between the reconstructed and input images to preserve sufficient anatomical structure information. Moreover, a non-parameter target-adaptive attention module is proposed to distinguish the unclear boundary by enhancing the feature-level contrast between rectal tumors and normal tissues. The experimental results indicate that the proposed method outperforms state-of-the-art approaches in rectal tumor and rectum segmentation tasks, with Dice coefficients of 84.91 % and 90.36 %, respectively, demonstrating its potential application value in clinical practice.

A Machine Learning Model Based on MRI Radiomics to Predict Response to Chemoradiation Among Patients with Rectal Cancer

BACKGROUND

With rectum-sparing protocols becoming more common for rectal cancer treatment, this study aimed to predict the pathological complete response (pCR) to preoperative chemoradiotherapy (pCRT) in rectal cancer patients using pre-treatment MRI and a radiomics-based machine learning approach.

METHODS

We divided MRI-data from 102 patients into a training cohort (n = 72) and a validation cohort (n = 30). In the training cohort, 52 patients were classified as non-responders and 20 as pCR based on histological results from total mesorectal excision.

RESULTS

We trained various machine learning models using radiomic features to capture disease heterogeneity between responders and non-responders. The best-performing model achieved a receiver operating characteristic area under the curve (ROC-AUC) of 73% and an accuracy of 70%, with a sensitivity of 78% and a positive predictive value (PPV) of 80%. In the validation cohort, the model showed a sensitivity of 81%, specificity of 75%, and accuracy of 80%.

CONCLUSIONS

These results highlight the potential of radiomics and machine learning in predicting treatment response and support the integration of advanced imaging and computational methods for personalized rectal cancer management.

Visualization analysis of research hotspots and trends in MRI-based artificial intelligence in rectal cancer

Background

Rectal cancer (RC) is one of the most common types of cancer worldwide. With the development of artificial intelligence (AI), the application of AI in preoperative evaluation and follow-up treatment of RC based on magnetic resonance imaging (MRI) has been the focus of research in this field. This review was conducted to develop comprehensive insight into the current research progress, hotspots, and future trends in AI based on MRI in RC, which remains to be studied.

Methods

Literature related to AI based on MRI and RC, as of November 2023, was obtained from the Web of Science Core Collection database. Visualization and bibliometric analyses of publication quantity and content were conducted to explore temporal trends, spatial distribution, collaborative networks, influential articles, keyword co-occurrence, and research directions.

Results

A total of 177 papers (152 original articles and 25 reviews) were identified from 24 countries/regions, 351 institutions, and 81 journals. Since 2019, the number of studies on this topic has rapidly increased. China and the United States have contributed the highest number of publications and institutions, cultivating the most intimate collaborative relationship. The highest number of articles derive from Sun Yat-sen University, while Frontiers in Oncology has published the highest number of relevant articles. Research on MRI-based AI in this field has mainly focused on preoperative diagnosis and prediction of treatment efficacy and prognosis.

Conclusions

This study provides an objective and comprehensive overview of the publications on MRI-based AI in RC and identifies the present research landscape, hotspots, and prospective trends in this field, which can provide valuable guidance for scholars worldwide.

Deformable Mapping of Rectal Cancer Whole-Mount Histology with Restaging MRI at Voxel Scale: A Feasibility Study

Purpose To develop a radiology-pathology coregistration method for 1:1 automated spatial mapping between preoperative rectal MRI and ex vivo rectal whole-mount histology (WMH). Materials and Methods This retrospective study included consecutive patients with rectal adenocarcinoma who underwent total neoadjuvant therapy followed by total mesorectal excision with preoperative rectal MRI and WMH from January 2019 to January 2022. A gastrointestinal pathologist and a radiologist established three corresponding levels for each patient at rectal MRI and WMH, subsequently delineating external and internal rectal wall contours and the tumor bed at each level and defining eight point-based landmarks. An advanced deformable image coregistration model based on the linearized iterative boundary reconstruction (LIBR) approach was compared with rigid point-based registration (PBR) and state-of-the-art deformable intensity-based multiscale spectral embedding registration (MSERg). Dice similarity coefficient (DSC), modified Hausdorff distance (MHD), and target registration error (TRE) across patients were calculated to assess the coregistration accuracy of each method. Results Eighteen patients (mean age, 54 years ± 13 [SD]; nine female) were included. LIBR demonstrated higher DSC versus PBR for external and internal rectal wall contours and tumor bed (external: 0.95 ± 0.03 vs 0.86 ± 0.04, respectively, P < .001; internal: 0.71 ± 0.21 vs 0.61 ± 0.21, P < .001; tumor bed: 0.61 ± 0.17 vs 0.52 ± 0.17, P = .001) and versus MSERg for internal rectal wall contours (0.71 ± 0.21 vs 0.63 ± 0.18, respectively; P < .001). LIBR demonstrated lower MHD versus PBR for external and internal rectal wall contours and tumor bed (external: 0.56 ± 0.25 vs 1.68 ± 0.56, respectively, P < .001; internal: 1.00 ± 0.35 vs 1.62 ± 0.59, P < .001; tumor bed: 2.45 ± 0.99 vs 2.69 ± 1.05, P = .03) and versus MSERg for internal rectal wall contours (1.00 ± 0.35 vs 1.62 ± 0.59, respectively; P < .001). LIBR demonstrated lower TRE (1.54 ± 0.39) versus PBR (2.35 ± 1.19, P = .003) and MSERg (2.36 ± 1.43, P = .03). Computation time per WMH slice for LIBR was 35.1 seconds ± 12.1. Conclusion This study demonstrates feasibility of accurate MRI-WMH coregistration using the advanced LIBR method. Keywords: MR Imaging, Abdomen/GI, Rectum, Oncology Supplemental material is available for this article. © RSNA, 2024.

Comparative Outcomes of Robotic Versus Open Proctectomy for Rectal Cancer at High Risk of Positive Circumferential Resection Margin

BACKGROUND

Concerns persist regarding the effectiveness of robotic proctectomy compared with open proctectomy for locally advanced rectal cancer with a high risk of circumferential resection margin involvement.

OBJECTIVE

Comparison of surrogate cancer outcomes after robotic versus open proctectomy in this subpopulation.

DESIGN

Retrospective cohort study.

SETTING

Three academic hospitals (Mayo Clinic Arizona, Florida, and Rochester) with data available through the Mayo Data Explorer platform.

PATIENTS

Patients at high risk of circumferential resection margin involvement were selected on the basis of the MRI-based definition from the MERCURY I and II trials.

MAIN OUTCOME MEASURES

Rate of pathologic circumferential resection margin involvement (≤1 mm), mesorectal grading, and rate of distal margin involvement.

RESULTS

Out of 413 patients, 125 (30%) underwent open and 288 (70%) underwent robotic proctectomy. Open proctectomy was significantly associated with a greater proportion of cT4 tumors (39.3% vs 24.8%, p = 0.021), multivisceral/concomitant resections (40.8% vs 18.4%, p < 0.001), and less frequent total neoadjuvant therapy use (17.1% vs 47.1%, p = 0.001). Robotic proctectomy was less commonly associated with pathologic circumferential resection margin involvement (7.3% vs 17.6%, p = 0.002), including after adjustment for cT stage, neoadjuvant therapy, and multivisceral resection (OR 0.326; 95% CI, 0.157-0.670, p = 0.002). Propensity score matching for 66 patients per group and related multivariable analysis no longer indicated any reduction of circumferential positive margin rate associated with robotic surgery ( p = 0.86 and p = 0.18). Mesorectal grading was comparable (incomplete mesorectum in 6% robotic proctectomy patients vs 11.8% open proctectomy patients, p = 0.327). All cases had negative distal resection margins.

LIMITATION

Retrospective design.

CONCLUSIONS

In patients with locally advanced rectal cancer at high risk of circumferential resection margin involvement, robotic proctectomy is an effective approach and could be pursued when technically possible as an alternative to open proctectomy. See Video Abstract .

RESULTADOS COMPARATIVOS ENTRE LA PROCTECTOMA ROBTICA Y LA PROCTECTOMA ABIERTA EN CASOS DE CNCER DE RECTO CON ALTO RIESGO DE MRGEN DE RESECCIN CIRCUNFERENCIAL POSITIVO

ANTECEDENTES:Persisten preocupaciones con respecto a la efectividad de la proctectomía robótica en comparación con la proctectomía abierta en casos de cáncer de recto localmente avanzado con un alto riesgo de margen de resección circunferencial positivo.OBJETIVO:Comparar los resultados en la subpoblación de portadores de cáncer luego de una proctectomía robótica versus una proctectomía abierta.DISEÑO:Estudio retrospectivo de cohortes.AJUSTE:Realizado en tres hospitales académicos (Mayo Clinic de Arizona, Florida y Rochester) a través de la plataforma Mayo Data Explorer.PACIENTES:Fueron seleccionados aquellos pacientes con alto riesgo de compromiso sobre el margen de resección circunferencial, según la definición de los Estudios Mercury I-II basada en la Imágen de Resonancia Magnética.MEDIDAS DE RESULTADO PRINCIPALES Y SECUNDARIAS:La tasa de compromiso patológico sobre el margen de resección circunferencial (≤1 mm), la clasificación mesorrectal y la tasa del compromiso del margen distal.RESULTADOS:De 413 pacientes, 125 (30%) fueron sometidos a una proctectomía abierta y 288 (70%) a proctectomía robótica. La proctectomía abierta se asoció significativamente con una mayor proporción de tumores cT4 (39,3% frente a 24,8%, p = 0,021), las resecciones multiviscerales/concomitantes fueron de 40,8% frente a 18,4%, p < 0,001 y una adminstración menos frecuente de terapia neoadyuvante total (17,1). % vs 47,1%, p = 0,001).La proctectomía robótica se asoció con menos frecuencia con la presencia de una lesión sobre el margen de resección circunferencial patológico (7,3% frente a 17,6%, p = 0,002), incluso después del ajuste por estadio cT, de la terapia neoadyuvante y de resección multivisceral (OR 0,326, IC 95% 0,157-0,670, p = 0,002). El apareado de propensión por puntuación en 66 pacientes por grupo y el análisis multivariable relacionado, no mostraron ninguna reducción en la tasa de margen positivo circunferencial asociado con la cirugía robótica ( p = 0,86 y p = 0,18). La clasificación mesorrectal fue igualmente comparable (mesorrecto incompleto en el 6% de los pacientes con RP frente al 11,8% de los pacientes con OP, p = 0,327). Todos los casos tuvieron márgenes de resección distal negativos.LIMITACIÓN:Diseño retrospectivo.CONCLUSIÓN:En pacientes con cáncer de recto localmente avanzado con alto riesgo de compromiso del margen de resección circunferencial, la proctectomía robótica es un enfoque eficaz y podría realizarse cuando sea técnicamente posible como alternativa a la proctectomía abierta. (Traducción-Dr. Xavier Delgadillo ).

The predicting value of post neoadjuvant treatment magnetic resonance imaging: a meta-analysis

INTRODUCTION

Neoadjuvant therapy has become standard of care for locally advanced rectal cancer patients. It is correlated with improved clinical and pathological outcomes, including significant tumor downstaging and organ preservation in certain patients. Magnetic resonance imaging (MRI), which has become the standard for pre-operative staging, is also used for clinical and pre-operative restaging following pre-operative treatment. In this meta-analysis, we aimed to evaluate the concordance between restaging MRI (following the completion of neoadjuvant therapy) and postoperative pathology result.

METHODS

We conducted a meta-analysis following the PRISMA 2020 guidelines. Two independent reviewers searched PubMed and Google Scholar for studies reporting restaging MRI results compared to pathological outcomes. Outcomes included tumor and nodal staging, circumferential resection margin (CRM) and pathological complete response (pCR).

RESULTS

Out of 25,000 studies found on the initial search; 33 studies were included. The studies were published between 2005 and 2023 and included 4100 patients (57.14% males). The median age was 62.45 years. The median interval between the conclusion of neoadjuvant treatment and the subsequent restaging MRI was 6 weeks (range 4.14-8.8 weeks). The pooled concordance rates between the restaging MRI and the pathological outcomes for ypT stage and ypN stage were 63.9% (54.5%-73.3%, I2 = 96.02%) and 60.9% (42.9%-78.9%, I2 = 98.96%), respectively. The pooled concordance for predicting pathological complete response was 70.4% (53.6%-87.1%, I2 = 98.21%). As for the circumferential resection margin (CRM), the pooled concordance was 78.2.% (71.6%-84.8%, I2 = 83.76%).

CONCLUSIONS

Our findings suggest that the concordance rates between restaging MRI and pathological outcomes in rectal cancer patients following neoadjuvant therapy are limited. Caregivers should take these results into consideration when making clinical decisions about these patients. More data should be gathered about the predictive value of MRI after total neoadjuvant therapy as well as immunotherapy in rectal cancer patients.

The role of MRI in radiotherapy planning: a narrative review "from head to toe"

Over the last few years, radiation therapy (RT) techniques have evolved very rapidly, with the aim of conforming high-dose volume tightly to a target. Although to date CT is still considered the imaging modality for target delineation, it has some known limited capabilities in properly identifying pathologic processes occurring, for instance, in soft tissues. This limitation, along with other advantages such as dose reduction, can be overcome using magnetic resonance imaging (MRI), which is increasingly being recognized as a useful tool in RT clinical practice. This review has a two-fold aim of providing a basic introduction to the physics of MRI in a narrative way and illustrating the current knowledge on its application "from head to toe" (i.e., different body sites), in order to highlight the numerous advantages in using MRI to ensure the best therapeutic response. We provided a basic introduction for residents and non-radiologist on the physics of MR and reported evidence of the advantages and future improvements of MRI in planning a tailored radiotherapy treatment "from head to toe". CRITICAL RELEVANCE STATEMENT: This review aims to help understand how MRI has become indispensable, not only to better characterize and evaluate lesions, but also to predict the evolution of the disease and, consequently, to ensure the best therapeutic response. KEY POINTS: MRI is increasingly gaining interest and applications in RT planning. MRI provides high soft tissue contrast resolution and accurate delineation of the target volume. MRI will increasingly become indispensable for characterizing and evaluating lesions, and to predict the evolution of disease.

The Role of Predictive and Prognostic MRI-Based Biomarkers in the Era of Total Neoadjuvant Treatment in Rectal Cancer

The role of magnetic resonance imaging (MRI) in rectal cancer management has significantly increased over the last decade, in line with more personalized treatment approaches. Total neoadjuvant treatment (TNT) plays a pivotal role in the shift from traditional surgical approach to non-surgical approaches such as 'watch-and-wait'. MRI plays a central role in this evolving landscape, providing essential morphological and functional data that support clinical decision-making. Key MRI-based biomarkers, including circumferential resection margin (CRM), extramural venous invasion (EMVI), tumour deposits, diffusion-weighted imaging (DWI), and MRI tumour regression grade (mrTRG), have proven valuable for staging, response assessment, and patient prognosis. Functional imaging techniques, such as dynamic contrast-enhanced MRI (DCE-MRI), alongside emerging biomarkers derived from radiomics and artificial intelligence (AI) have the potential to transform rectal cancer management offering data that enhance T and N staging, histopathological characterization, prediction of treatment response, recurrence detection, and identification of genomic features. This review outlines validated morphological and functional MRI-derived biomarkers with both prognostic and predictive significance, while also exploring the potential of radiomics and artificial intelligence in rectal cancer management. Furthermore, we discuss the role of rectal MRI in the 'watch-and-wait' approach, highlighting important practical aspects in selecting patients for non-surgical management.

Local Excision for organ preservation in early REctal cancer with No Adjuvant treatment (LORENA Trial): prospective observational study protocol

INTRODUCTION

Local resection (LR) is an alternative to total mesorectal excision (TME) that avoids its associated morbidity to the detriment of oncological radicality in early stages of rectal cancer. There are several conditioning factors for the success of this strategy, such as poor prognosis histological factors (PPHF), involvement of resection margins, clinical under staging, or complications that may lead to the indication for radical surgery with TME.

PATIENTS AND METHOD

An international multicenter prospective observational open-label study has been designed. Consecutive patients diagnosed with early rectal cancer (cT1N0 on MRI +/- endorectal ultrasound) whose lower limit is a maximum of 2 cm proximal to the ano-rectal junction will be included. The primary objective of the study is to determine the overall prevalence of PPHF after LR and requiring TME or postoperative radio-chemotherapy.

DISCUSSION

The prevalence of PPHF conditioning the success of LR in early distal rectal cancer has been scarcely studied in the literature, and there are very few prospective data. Considering the increasing interest in the watch and wait strategy in rectal cancer and its possible application in early-stage tumors, it seems necessary to know this information. The results of this study will help guide clinical practice in patients with early distal rectal cancer. It will also provide quality information for the design of future comparative studies to improve organ preservation success in these patients.

TRIAL REGISTRATION NUMBER

NCT05927584.

Journey through the Decades: The Evolution in Treatment and Shared Decision Making for Locally Advanced Rectal Cancer

The management of locally advanced rectal cancer has undergone significant transformations over the decades and optimal treatment approaches continue to evolve. There have been numerous advances in surgery, chemotherapy, and radiation therapy from the first description of the abdominoperineal resection in 1908, timing of chemotherapy and radiation therapy in the late 20th and early 21st century, and most recently, the introduction of organ preservation or nonoperative management in 2004. Alongside these advancements, the concept of shared decision making in medicine has evolved, prompting a focus on patient-centered care. This evolution in practice has been fueled by a growing recognition of the importance of patient autonomy and the alignment of treatment options with patients' values and preferences. With the growing number of possible treatment options, variability in patient counseling exists, highlighting the need for a standardized approach to shared decision making in locally advanced rectal cancer. This narrative review will describe the evolution of treatment options of locally advanced rectal cancer as well as the concept of shared decision making and decision aids, and will introduce a decision aid for patients with locally advanced rectal cancer who have achieved a complete clinical response and are eligible for watch and wait.

Imaging and Metabolic Diagnostic Methods in the Stage Assessment of Rectal Cancer

Rectal cancer (RC) is a prevalent malignancy with significant morbidity and mortality rates. The accurate staging of RC is crucial for optimal treatment planning and patient outcomes. This review aims to summarize the current literature on imaging and metabolic diagnostic methods used in the stage assessment of RC. Various imaging modalities play a pivotal role in the initial evaluation and staging of RC. These include magnetic resonance imaging (MRI), computed tomography (CT), and endorectal ultrasound (ERUS). MRI has emerged as the gold standard for local staging due to its superior soft tissue resolution and ability to assess tumor invasion depth, lymph node involvement, and the presence of extramural vascular invasion. CT imaging provides valuable information about distant metastases and helps determine the feasibility of surgical resection. ERUS aids in assessing tumor depth, perirectal lymph nodes, and sphincter involvement. Understanding the strengths and limitations of each diagnostic modality is essential for accurate staging and treatment decisions in RC. Furthermore, the integration of multiple imaging and metabolic methods, such as PET/CT or PET/MRI, can enhance diagnostic accuracy and provide valuable prognostic information. Thus, a literature review was conducted to investigate and assess the effectiveness and accuracy of diagnostic methods, both imaging and metabolic, in the stage assessment of RC.

Modified neoadjuvant rectal score as a novel prognostic model for rectal cancer patients who underwent chemoradiotherapy

BACKGROUND

The neoadjuvant rectal score (NAR score) has recently been proposed as a better prognostic model than the conventional TNM classification for rectal cancer patients that have undergone neoadjuvant chemoradiotherapy. We recently developed an apoptosis-detection technique for assessing the viability of residual tumors in resected specimens after chemoradiotherapy. This study aimed to establish an improved prognostic classification by combining the NAR score and the assessment of the apoptosis of residual cancer cells.

METHODS

We retrospectively enrolled 319 rectal cancer patients who underwent chemoradiotherapy followed by radical surgery. The recurrence-free survival and overall survival of the four models were compared: TNM stage, NAR score, modified TNM stage by re-staging according to cancer cell viability, and modified NAR score also by re-staging.

RESULTS

Downstaging of the ypT stage was observed in 15.5% of cases, whereas only 4.5% showed downstaging of ypN stage. C-index was highest for the modified NAR score (0.715), followed by the modified TNM, TNM, and NAR score. Similarly, Akaike's information criterion was smallest in the modified NAR score (926.2), followed by modified TNM, TNM, and NAR score, suggesting that the modified NAR score was the best among these four models. The overall survival results were similar: C-index was the highest (0.767) and Akaike's information criterion was the smallest (383.9) for the modified NAR score among the four models tested.

CONCLUSION

We established a novel prognostic model, for rectal cancer patients that have undergone neoadjuvant chemoradiotherapy, using a combination of apoptosis-detecting immunohistochemistry and neoadjuvant rectal scores.

Deep learning for MRI lesion segmentation in rectal cancer

Rectal cancer (RC) is a globally prevalent malignant tumor, presenting significant challenges in its management and treatment. Currently, magnetic resonance imaging (MRI) offers superior soft tissue contrast and radiation-free effects for RC patients, making it the most widely used and effective detection method. In early screening, radiologists rely on patients' medical radiology characteristics and their extensive clinical experience for diagnosis. However, diagnostic accuracy may be hindered by factors such as limited expertise, visual fatigue, and image clarity issues, resulting in misdiagnosis or missed diagnosis. Moreover, the distribution of surrounding organs in RC is extensive with some organs having similar shapes to the tumor but unclear boundaries; these complexities greatly impede doctors' ability to diagnose RC accurately. With recent advancements in artificial intelligence, machine learning techniques like deep learning (DL) have demonstrated immense potential and broad prospects in medical image analysis. The emergence of this approach has significantly enhanced research capabilities in medical image classification, detection, and segmentation fields with particular emphasis on medical image segmentation. This review aims to discuss the developmental process of DL segmentation algorithms along with their application progress in lesion segmentation from MRI images of RC to provide theoretical guidance and support for further advancements in this field.

Low anterior resection syndrome phenotypes-Different symptom profiles for different patients

AIM

Attention is increasingly being turned to functional outcomes as being central to colorectal cancer (CRC) survivorship. The current literature may underestimate the impact of evacuatory dysfunction on patient satisfaction with bowel function after anterior resection (AR) for CRC. The aim of this study was to investigate the impact of post-AR symptoms of storage and evacuatory dysfunction on patient satisfaction and health-related quality of life (HRQoL).

METHOD

A cross-sectional study was performed at an Australian hospital of patients post-AR for CRC (2012-2021). The postoperative bowel function scores used were: low anterior resection syndrome (LARS), St Mark's incontinence, Cleveland Clinic constipation and Altomare obstructive defaecation syndrome scores. Eight 'storage' and 'evacuatory' dysfunction symptoms were derived. A seven-point Likert scale measured patient satisfaction. The SF36v2® measured HRQoL. Linear regression assessed the association between symptoms, patient satisfaction and HRQoL.

RESULTS

Overall, 248 patients participated (mean age 70.8 years, 57.3% male), comprising 103 with rectal cancer and 145 with sigmoid cancer. Of the symptoms that had a negative impact on patient satisfaction, six reflected evacuatory dysfunction, namely excessive straining (p < 0.001), one or more unsuccessful bowel movement attempt(s)/24 h (p < 0.001), anal/vaginal digitation (p = 0.005), regular enema use (p = 0.004), toilet revisiting (p = 0.004) and >10 min toileting (p = 0.004), and four reflected storage dysfunction, namely leaking flatus (p = 0.002), faecal urgency (p = 0.005), use of antidiarrhoeal medication (p = 0.001) and incontinence-related lifestyle alterations (p < 0.001). A total of 130 patients (53.5%) had 'no LARS', 56 (23.1%) had 'minor LARS' and 57 (23.4%) had 'major LARS'. Fifty-seven (44.5%) patients classified as having 'no LARS' had evacuatory dysfunction.

CONCLUSION

Postoperative storage and evacuatory dysfunction symptoms have an adverse impact on patient satisfaction and HRQoL post-AR. The importance of comprehensively documenting symptoms of evacuatory dysfunction is highlighted. Further research is required to develop a patient satisfaction-weighted LARS-specific HRQoL instrument.

Primary staging of rectal cancer on MRI: an updated pictorial review with focus on common pitfalls and current controversies

Magnetic resonance imaging (MRI) plays a pivotal role in primary staging of rectal cancer, enabling the determination of appropriate management strategies and prediction of patient outcomes. However, inconsistencies and pitfalls exist in various aspects, including rectal anatomy, MRI protocols and strategies for artifact resolution, as well as in T- and N-staging, all of which limit the diagnostic value of MRI. This narrative and pictorial review offers a comprehensive overview of factors influencing primary staging of rectal cancer and the role of MRI in assessing them. It highlights the significance of the circumferential resection margin and its relationship with the mesorectal fascia, as well as the prognostic role of extramural venous invasion and tumor deposits. Special attention is given to tumors of the lower rectum due to their complex anatomy and the challenges they pose in MRI staging. The review also addresses current controversies in rectal cancer staging and the need for personalized risk stratification. In summary, this review provides valuable insights into the role of MRI in the primary staging of rectal cancer, emphasizing key aspects for accurate assessment to enhance patient outcomes.

Performance of CT in the locoregional staging of colon cancer: detailed radiology-pathology correlation with special emphasis on tumor deposits, extramural venous invasion and T staging

PURPOSE

To investigate the performance of computed tomography (CT) in the local staging of colon cancer in different segments, with emphasis on parameters that have been found to be significant for rectal cancer, namely, extramural venous invasion (EMVI) and tumor deposits (TDs).

METHODS

CT and pathology data from 137 patients were independently reviewed by radiology and pathology teams. The performance of CT in categorizing a given patient into good, versus poor prognostic groups was assessed for each segment, as well as the presence of lymph nodes (LNs), TDs and EMVIs. Discordant cases were re-evaluated to determine potential sources of error. Elastic stain was applied for EMVI discordance.

RESULTS

The T staging accuracy was 80.2%. For T stage stratification, CT performed slightly better in the left colon, and the lowest accuracy was in the transverse colon. Under-staging was more common (in 12.4%), and most of the mis-staged cases were in sigmoid colon. According to the first comprehensive correlative analysis, the sensitivity, specificity, and accuracy of CT for detecting TDs were found to be 57.9%, 92.4%, 87.6%, respectively. These figures were 44.7%, 72.7%, and 63.5% for LN, and 58.5%, 82.1% and 73% for EMVI. The detection rate was better for multifocal EMVI. The detection rate was also comparable (although substantially underestimated) for LNs, with the half of the LNs missed by CT being < 5 mm. Four patients that were classified as TD by CT, disclosed to be LNs by pathology. Correlative analysis led to refinement of the pathology criteria, with subsequent modifications of the initial reports in 13 (9.5%) patients.

CONCLUSION

Overall, CT performed well in the evaluation of colon cancer, as did TD and EMVI. It is advisable to include these parameters in CT-based staging. Radiologists should be aware of the pitfalls that occur more commonly in different segments.

MRI-based radiomics feature combined with tumor markers to predict TN staging of rectal cancer

The aim of this study is to evaluate the predictive ability of MRI-based radiomics combined with tumor markers for TN staging in patients with rectal cancer and to develop a prediction model for TN staging. A total of 190 patients with rectal adenocarcinoma who underwent total mesorectal excision at the First Affiliated Hospital of the Air Force Medical University between January 2016 and December 2020 were included in the study. An additional 54 patients from a prospective validation cohort were included between August 2022 and August 2023. Preoperative tumor markers and MRI imaging data were collected from all enrolled patients. The 190 patients were divided into a training cohort (n = 133) and a validation cohort (n = 57). Radiomics features were extracted by outlining the region of interest (ROI) on T2WI sequence images. Feature selection and radiomics score (Rad-score) construction were performed using least absolute shrinkage and selection operator regression analysis (LASSO). The postoperative pathology TNM stage was used to differentiate locally advanced rectal cancer (T3/4 or N1/2) from locally early rectal cancer (T1/2, N0). Logistic regression was used to construct separate prediction models for T stage and N stage. The models' predictive performance was evaluated using DCA curves and calibration curves. The T staging model showed that Rad-score, based on 8 radiomics features, was an independent predictor of T staging. When combined with CEA, tumor diameter, mesoretal fascia (MRF), and extramural venous invasion (EMVI), it effectively differentiated between T1/2 and T3/4 stage rectal cancers in the training cohort (AUC 0.87 [95% CI: 0.81-0.93]). The N-staging model found that Rad-score, based on 10 radiomics features, was an independent predictor of N-staging. When combined with CA19.9, degree of differentiation, and EMVI, it effectively differentiated between N0 and N1/2 stage rectal cancers. The training cohort had an AUC of 0.84 (95% CI: 0.77-0.91). The calibration curves demonstrated good precision between the predicted and actual results. The DCA curves indicated that both sets of predictive models could provide net clinical benefits for diagnosis. MRI-based radiomics features are independent predictors of T staging and N staging. When combined with tumor markers, they have good predictive efficacy for TN staging of rectal cancer.

Diagnostic performance of dynamic contrast-enhanced magnetic resonance imaging parameters and serum tumor markers in rectal carcinoma prognosis

BACKGROUND

Rectal carcinoma (RC), one of the most common malignancies globally, presents an increasing incidence and mortality year by year, especially among young people, which seriously affects the prognosis and quality of life of patients. At present, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters and serum carbohydrate antigen 19-9 (CA19-9) and CA125 Levels have been used in clinical practice to evaluate the T stage and differentiation of RC. However, the accuracy of these evaluation modalities still needs further research. This study explores the application and value of these methods in evaluating the T stage and differentiation degree of RC.

AIM

To analyze the diagnostic performance of DCE-MRI parameters combined with serum tumor markers (TMs) in assessing pathological processes and prognosis of RC patients.

METHODS

A retrospective analysis was performed on 104 RC patients treated at Yantai Yuhuangding Hospital from May 2018 to January 2022. Patients were categorized into stages T1, T2, T3, and T4, depending on their T stage and differentiation degree. In addition, they were assigned to low (L group) and moderate-high differentiation (M + H group) groups based on their differentiation degree. The levels of DCE-MRI parameters and serum CA19-9 and CA125 in different groups of patients were compared. In addition, the value of DCE-MRI parameters [volume transfer constant (Ktrans), rate constant (Kep), and extravascular extracellular volume fraction (Ve) in assessing the differentiation and T staging of RC patients was discussed. Furthermore, the usefulness of DCE-MRI parameters combined with serum CA19-9 and CA125 Levels in the evaluation of RC differentiation and T staging was analyzed.

RESULTS

Ktrans, Ve, CA19-9 and CA125 were higher in the high-stage group and L group than in the low-stage group and M + H Group, respectively (P < 0.05). The areas under the curve (AUCs) of the Ktran and Ve parameters were 0.638 and 0.694 in the diagnosis of high and low stages, respectively, and 0.672 and 0.725 in diagnosing moderate-high and low differentiation, respectively. The AUC of DCE-MRI parameters (Ktrans + Ve) in the diagnosis of high and low stages was 0.742, and the AUC in diagnosing moderate-high and low differentiation was 0.769. The AUCs of CA19-9 and CA-125 were 0.773 and 0.802 in the diagnosis of high and low stages, respectively, and 0.834 and 0.796 in diagnosing moderate-high and low differentiation, respectively. Then, we combined DCE-MRI (Ktrans + Ve) parameters with CA19-9 and CA-125 and found that the AUC of DCE-MRI parameters plus serum TMs was 0.836 in the diagnosis of high and low stages and 0.946 in the diagnosis of moderate-high and low differentiation. According to the Delong test, the AUC of DCE-MRI parameters plus serum TMs increased significantly compared with serum TMs alone in the diagnosis of T stage and differentiation degree (P < 0.001).

CONCLUSION

The levels of the DCE-MRI parameters Ktrans and Ve and the serum TMs CA19-9 and CA125 all increase with increasing T stage and decreasing differentiation degree of RC and can be used as indices to evaluate the differentiation degree of RC in clinical practice. Moreover, the combined evaluation of the above indices has a better effect and more obvious clinical value, providing important guiding importance for clinical condition judgment and treatment selection.

PDCD4-induced oxidative stress through FGR/NF-κB axis in rectal cancer radiotherapy-induced AKI

This study aimed to investigate the molecular mechanism of the effect of PDCD4 on radiotherapy-induced acute kidney injury (AKI) in rectal cancer through the regulation of FGR/NF-κB signaling. Differentially expressed genes were identified using Gene Expression Omnibus (GEO) datasets (GSE90627 for rectal cancer and GSE145085 for AKI) and R software. The human renal tubular epithelial cell line, HK-2, was used to establish an in vitro model of radiotherapy-induced AKI. RT-qPCR and western blotting were used to detect gene and protein expression levels, respectively. Cell proliferation and apoptosis were assessed using the CCK-8 assay and flow cytometry, respectively. The malondialdehyde and superoxide dismutase levels in the cell culture supernatants were determined. Additionally, an in vivo AKI model was established using BALB/c mice, and kidney tissue morphology, expression of the renal injury molecule KIM-1, apoptosis of renal tubular cells, and TAS and TOS in serum were evaluated. Bioinformatics analysis revealed the upregulated expression of PDCD4 in AKI. In vitro experiments demonstrated that PDCD4 induced apoptosis in renal tubular cells by promoting FGR expression, which activated the NF-κB signaling pathway and triggered an oxidative stress response. In vivo animal experiments confirmed that PDCD4 promoted oxidative stress response and radiotherapy-induced AKI through the activation of the FGR/NF-κB signaling pathway. Silencing PDCD4 attenuated radiotherapy-induced AKI. Our findings suggest that PDCD4 may induce radiotherapy-induced AKI in rectal cancer by promoting FGR expression, activating the NF-κB signaling pathway, and triggering an oxidative stress response.