Diagnostic Accuracy of CT for Local Staging of Colon Cancer: A Systematic Review and Meta-Analysis. AJR Am J Roentgenol. 2016;207:984-995. [PMID: 27490941 DOI: 10.2214/ajr.15.15785]

Computed Tomography Colonography: 2025 Update

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the United States. Most cases arise from polyps, which can be detected and removed before becoming cancerous. Computed tomography colonography (CTC), also known as virtual colonoscopy, was first introduced in 1994 as a minimally invasive method for CRC screening and diagnosis. This 2025 update on CTC will focus on (1) techniques and dose reduction strategies, (2) image display methods, (3) reporting and classification systems, (4) tumor staging capabilities, (5) integration of advanced imaging techniques, and (6) cost-effectiveness and reimbursement.

Advancing colorectal cancer diagnosis: The role of tumor-derived serum galanin and haptoglobin as novel biomarkers

BACKGROUND

Colorectal cancer (CRC) is a widespread and serious global malignancy. This study aimed to investigate the clinical relevance of galanin (GAL) and haptoglobin (HP) as new diagnostic CRC biomarkers.

METHODS

An enzyme-linked immunosorbent assay was used to determine the GAL and HP levels in the serum of 88 patient with CRC and 88 healthy controls. The carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) contents were quantitatively evaluated via electrochemiluminescence assay. Receiver operating characteristic (ROC) curves were created to identify the diagnostic importance of single and combined CRC detection. The patients' relevant diagnostic and treatment data were collected from their medical records. Statistical analysis methods were employed to examine the relationship between these indicators and the clinical pathological parameters.

RESULTS

Patients with CRC exhibited significantly decreased and increased serum GAL and HP levels, respectively, compared with the healthy controls (P < 0.0001 for both). Furthermore, the HP level was positively correlated with tumor T stage (P = 0.0124). The area under the curve (AUC) of the ROC values for GAL and HP was 0.744 and 0.712, respectively, indicating their diagnostic efficiency. The combination of GAL and HP increased the AUC to 0.753, and when both were integrated with CEA and CA19-9, the AUC further increased to 0.893.

CONCLUSION

This study shows that serum GAL and HP can be used as potential noninvasive diagnostic biomarkers for CRC.

Rapid, label-free detection of colorectal cancer with an aberration-free line scanning confocal Raman imager

A self-developed aberration-free line scanning confocal Raman imager (AFLSCRI) with a spectral resolution of 0.12 nm and a spatial resolution of 2 μm is utilized to diagnose colorectal cancer. The tissues were categorized into four subgroups (typical tissue, lipid-rich tissue, fat-rich tissue, and collagen-rich tissue) and were successfully distinguished with our Raman imaging results. Compared to traditional point-scanning Raman spectroscopy, this imager offers a much faster speed with high spectral resolution while maintaining a similar spatial resolution. The Raman spectroscopy results of the same sample of colorectal cancer remain stable and unaffected even measured after six months. The molecular composition of the tissues was analyzed, and potential biomarkers such as carotenoids and protein structures were identified for four different types of colorectal tissues. When combined with machine learning algorithms, an accuracy of 92.8% was achieved in identifying 14 pairs of normal/cancer samples. These results highlight the great potential of the AFLSCRI in label-free, rapid, and non-invasive medical diagnosis.

Colon cancer biology and treatment in the era of precision oncology: A primer for Radiologists

In the era of precision oncology, systemic therapies for colon cancer are becoming increasingly biomarker-led, with implications for patients in the neoadjuvant, adjuvant and metastatic settings. As the landscape for colon cancer treatment evolves and becomes more complex, it is important that all members of the multidisciplinary team keep abreast of developments to ensure the most effective care is delivered to patients. As core members of the colorectal multidisciplinary team, Radiologists play a central role throughout the patient journey. This review serves as an educational summary of current and emerging treatment pathways in colon cancer, standards for biomarker testing, mechanisms of action for key drugs, important treatment-related complications, relevant tumour biology that underpins patterns of disease and treatment response, and the specific implications systemic therapies have for cancer imaging and Radiologists. We also highlight the increasing role for radiology in patient stratification and the importance of imaging biomarkers. It is crucial that Radiologists understand the current landscape of colon cancer treatment and emerging strategies on the horizon in clinical trials. Only through engagement across the wider multidisciplinary team will we deliver true personalised medicine for patients with colon cancer.

Neoadjuvant chemotherapy in locally advanced colon cancer: A systematic review with proportional meta-analysis

Neoadjuvant chemotherapy is suggested in locally advanced colon cancer. Data on improved long-term oncological outcomes are lacking, which hampers the implementation in clinical practice. This systematic review provides an overview of the benefits and drawbacks of neoadjuvant chemotherapy in patients with locally advanced colon cancer. A systematic literature search was performed using Embase (OVID), MEDLINE (OvidSP), and the Cochrane Library. Studies reporting on the efficacy of neoadjuvant chemotherapy in patients with operable, locally advanced colon cancer without metastases at the time of diagnosis were considered eligible for inclusion. An overview of short- and long-term outcomes of neoadjuvant chemotherapy is provided based on available literature. Additionally, proportional meta-analyses were performed using MedCalc Statistical Software version 19.2.6. A total of 17 unique studies were included in this review, 3 randomised controlled trials and 14 prospective single-arm or retrospective studies. The maximum reported dropout before surgery was 7.8 % in the neoadjuvant chemotherapy group. A histopathological complete response after neoadjuvant chemotherapy was observed in 0-4.8 % of the patients. The occurrence of anastomotic leaks was less than 8 % for both patients treated with neoadjuvant chemotherapy and patients treated with upfront surgery. Neoadjuvant chemotherapy is a safe alternative for adjuvant chemotherapy based on the dropout rate before surgery and the peri-operative morbidity and peri-operative mortality. Robust long-term survival outcomes are lacking and serious concerns regarding the risk of overtreatment have been expressed. Hence, neoadjuvant chemotherapy might be considered in a select group of patients with locally advanced colon cancer.

High-performance CT features supporting accurate pre-operative tumor staging in colon cancer

Background and aims

Accurate pre-treatment tumor staging is essential for treatment decision-making. Multi-slice spiral computed tomography (CT) is currently the standard method for pre-operative clinical tumor staging, but accurately applying the CT findings in tumor staging remains a challenge due to the poor pathological understanding of the CT signs. We aimed to pathologically interpret the key CT findings in order to identify reliable markers for pre-treatment staging of colon cancer.

Patients and methods

The following CT features from 136 colon adenocarcinomas were analyzed: colon wall pliability, outline contour, pericolic fat attenuations and vascularity, tumor fusion with adjacent organs, ascites, tumor size, and relevance between tumor and retroperitoneal fascia. These CT features were corroborated with histopathological findings. The diagnostic performance of these was further analyzed.

Results

Based on the postoperative pathological tumor staging (pT), 136 colon adenocarcinomas were classified into four stages: pT1 (n = 5), pT2 (n = 7), pT3 (n = 96), and pT4 (n = 28). Key findings include the following: (1) soft colon wall is a characteristic of the pT1 tumors, whereas stiff colon wall is a characteristic of the pT2~pT4 tumors; pathologically, stiff colon wall reflects the infiltration of tumor cells with desmoplastic reaction (DR) in muscularis propria; (2) small protuberances may help exclude the pT2 tumors. Histopathologically, small protuberances in pT2 cancer represent the pure DR on the surface of lamina propria, whereas the small protuberances in pT3~pT4 cancers represent the sub-serosal or extra-serosal cancer cell foci enwrapped by DR; (3) the presence of large protuberances, extensive reticulonodular fat stranding, and fusion with surrounding organs and ascites are diagnostic of pT4 tumors; and (4) the presence of extra-fascial nodules/streaks on CT scan could accurately diagnose the ascending/descending colon cancer of pT4 stage. Histologically, the presence of the above five CT features (large protuberances, extensive reticulonodular fat stranding, fusion with surrounding organs, ascites, and extra-fascial nodules/streaks) reflect the farther and deeper infiltration of tumor cells in serosa or retroperitoneal fascia involvement.

Conclusion

Our studies have identified multiple CT features that are practically useful in identifying and differentiating different stages of colon cancer prior to surgical procedures. These high-performance markers will provide valuable insights to the clinicians in making appropriate decisions in the management of patients with colon cancer.

Impact of hospital volume on survival in patients with locally advanced colon cancer - A Dutch population-based study

AIM

Locally advanced colon cancer (LACC) often necessitates complex prognosis-determining treatment. This study investigated the impact of hospital volume on short- and long-term outcomes following surgery for LACC.

METHOD

Data involving all patients with LACC categorized as clinical T4 and/or N2, between 2015 and 2019 in the Netherlands, were extracted from the Netherlands Cancer Registry. Hospitals were stratified into low volume (1-19 LACC resections per year), medium volume (20-29 LACC resections per year) and high volume (≥30 LACC resections per year). Data were analysed using Kaplan-Meier curves, logistic regression analysis and Cox-regression models.

RESULTS

A total of 49 298 patients were diagnosed with colon cancer, of whom 9206 (18.7%) had locally advanced disease. Of these 9206 patients, resection was performed in 8537 with a median age of 71 (interquartile range: 63-78) years. Patients were more likely to undergo laparoscopic procedures in high-volume hospitals than in low-volume hospitals (OR = 1.28, 95% CI: 1.12-1.46). No risk differences in anastomotic leakage or postoperative 90-day mortality were observed according to hospital volume. Five-year overall survival rates were comparable among high-, medium- and low-volume hospitals (58.7% vs. 58.0% vs. 60.0%, p = 0.62). Hospital volume was not associated with overall survival in multivariable analysis. Independent predictors of worse overall survival included older age, higher American Society of Anaesthesiologists score, emergency/urgent setting, anastomotic leakage, higher pTNM status, involved resection margins and no adjuvant chemotherapy.

CONCLUSION

Despite the complexity of surgical treatment, hospital volume was not associated with survival in LACC. Hospital volume might be an imperfect surrogate for quality assessment.

Tailored-surgery for locally advanced colon cancer based on 3D mathematical reconstruction surgical planner: Observational comparative non-randomized study

BACKGROUND

This study investigates the effectiveness of a three-dimensional reconstruction mathematical model (3D-IPR) for preoperative planning in locally advanced colon cancer (LACC) with threatened surgical margins. The objective was to evaluate the utility of a 3D-IPR surgical planner tool in cases of LACC with threatened surgical margins. Additionally, the study aims to compare the diagnostic accuracy of the 3D-IPR model against conventional CT scans in determining the infiltration of neighboring structures.

METHODS

This Single-center, prospective, observational, comparative, non-randomized study. INCLUSIóN CRITERIA: Patients over 18 years old undergoing surgery for LACC as indicated by a radiologist's analysis of CT scans. Preoperative confirmation of neoplasm by colonoscopy.

EXCLUSION CRITERIA

patients who had received neoadjuvant chemotherapy, suspected carcinomatosis on preoperative CT and patients with unresectable tumors. All patients were selected consecutively.

PROCEDURES

Intervention involved using a 3D-IPR model as a surgical planning tool for patients with LACC. The 3D-IPR provided detailed metrics about the tumor and surrounding structures to assist in surgical planning. Surgical procedures were guided by the radiological assessments from CT scans and intraoperative findings, with surgeries categorized based on surgical margins as R0, R1, or R2. The primary endpoint was the diagnostic accuracy of the 3D-IPR model in determining tumor infiltration of neighboring structures compared to conventional CT scans. The measure used to assess this outcome was the definitive pathological report of tumor infiltration, which served as the gold standard for comparison. Demographic, intraoperative, morbidity, mortality, and pathological data were analyzed.

RESULTS

21 patients were assessed, 1 excluded with a final sample of 20 patients. 3D-IPR model demonstrated higher diagnostic accuracy for tumor infiltration of neighboring structures compared to conventional CT scans, with sensitivity, specificity, Positive Predictive Value, and Negative Predictive Value of 70 %, 90 %, 87.5 %, and 75 %, respectively. Surgeries were predominantly minimally invasive (70 %), with no major complications or mortality within 30 days, and a 0 % conversion rate to open surgery.

CONCLUSIONS

The 3D-IPR model significantly enhances preoperative planning accuracy, reducing the risk of incomplete resections and improving surgical outcomes. This technology offers a reliable basis for surgical decisions, potentially improving patient prognosis and survival rates.

Preoperative CT lymph node size as a predictor of nodal metastasis in resectable Colon cancer: a retrospective study of 694 patients

PURPOSE

This study aimed to investigate the efficacy of measuring lymph node size on preoperative CT imaging to predict pathological lymph node metastasis in patients with colon cancer to enhance diagnostic accuracy and improve treatment planning by establishing more reliable assessment methods for lymph node metastasis.

METHODS

We retrospectively analyzed 1,056 patients who underwent colorectal resection at our institution between January 2004 and March 2020. From this cohort, 694 patients with resectable colon cancer were included in the study. We analyzed the relationship between lymph node size on preoperative CT imaging and lymph node metastasis identified on postoperative pathological examination.

RESULTS

The optimal cutoff values for the maximum long diameter and short diameter of regional lymph nodes on preoperative CT were identified as 6.5 mm and 5.5 mm, respectively, with an AUC of 0.7794 and 0.7755, respectively. Notably, the predictive accuracy varied by tumor location. Higher cutoff values were observed in the right-sided colon (maximum long diameter: 7.7 mm, maximum short diameter: 5.9 mm) compared to the left-sided colon (maximum long diameter: 5.8 mm, maximum short diameter: 5.2 mm).

CONCLUSION

Lymph node size on preoperative CT is a significant predictor of pathological lymph node metastasis in colon cancer. Notably, the optimal cutoff values for predicting lymph node metastasis vary depending on the specific region within the colon.

Diagnostic accuracy and reliability of CT-based Node-RADS for colon cancer

OBJECTIVE

The Node-RADS classification was recently published as a classification system to better characterize lymph nodes in oncological imaging. The present analysis investigated the diagnostic benefit of the Node-RADS classification of staging computed tomography (CT) images to categorize and stage lymph nodes in patients with colon cancer.

MATERIALS AND METHODS

All patients were surgically resected and the lymph nodes were histopathological analyzed. All investigated lymph nodes were scored in accordance to the Node-RADS classification by two experienced radiologists. Interreader variability was assessed with Cohen's kappa analysis, discrimination analysis was performed with Mann-Whitney-U test and diagnostic accuracy was assessed with receiver-operating characteristics (ROC) curve analysis.

RESULTS

Overall, 108 patients (n = 49 females, 45.3%) with a mean age of 70.08 ± 14.34 years were included. In discrimination analysis, the total Node-RADS score showed statistically significant differences between N- and N + stage (for reader 1: mean 1.89 ± 1.09 score for N- versus 2.93 ± 1.62 score for N+, for reader 2: 1.33 ± 0.48 score for N- versus 3.65 ± 0.94 score for N+, p = 0.001, respectively). ROC curve analysis for lymph node discrimination showed an area under the curve of 0.68. A threshold value of 2 resulted in a sensitivity of 0.62 and a specificity of 0.71.

CONCLUSION

Node-RADS score derived from staging CT shows only limited diagnostic accuracy to correctly predict nodal positivity in colon cancer. The interreader variability seems to be high and should question the clinical translation for this tumour entity.

Evaluation of colon cancer prognostic factors by CT and MRI: an up-to-date review

Colorectal cancer (CRC) is a significant global health concern. Prognostication of CRC traditionally relies on the Union for International Cancer Control (UICC) and American Joint Committee on Cancer (AJCC) TNM staging classifications, yet clinical outcomes often vary independently of stage. Despite similarities, rectal and colon cancers are distinct in their diagnostic methodologies and treatments, with MRI and CT scans primarily used for staging rectal and colon cancers, respectively. This paper examines the challenges in accurately assessing prognostic factors of colon cancer such as primary tumor extramural extension, retroperitoneal surgical margin (RSM) involvement, extramural vessel invasion (EMVI), and lymph node metastases through preoperative CT and MRI. It highlights the importance of these factors in risk stratification, treatment decisions, and surgical planning for colon cancer patients. Advancements in imaging techniques are crucial for improving clinical management and optimizing patient outcomes, underscoring the necessity for ongoing research to refine diagnostic methods and incorporate novel findings into practice.

Accuracy of Clinical Staging of Localized Colon Cancer: A National Cancer Database Cohort Analysis

BACKGROUND

This study aimed to assess concordance between clinical and pathologic assessment of colon cancer.

PATIENTS AND METHODS

A retrospective cohort analysis of patients with stage I-III colon cancer in the National Cancer Database (2010-2019) was conducted. Concordance between clinical and pathologic assessment of colon cancer was calculated using Kappa coefficients and 95% confidence intervals (CIs).

RESULTS

A total of 125,473 patients (51.2% female; mean age 68.2 years) were included. There was moderate concordance between clinical and pathologic T stage (Kappa = 0.606, 95%CI: 0.602-0.609) and between clinical and pathologic N stage (Kappa = 0.506, 95%CI: 0.501-0.511). For right-sided colon cancer, there was moderate agreement between clinical and pathologic T stage (Kappa = 0.594, 95%CI: 0.589-0.599) and N stage (Kappa = 0.530, 95%CI: 0.523-0.537). For left-sided colon cancer, there was substantial agreement between clinical and pathologic T stage (Kappa = 0.624, 95%CI: 0.619-0.630) and moderate agreement between N stage (Kappa 0.472, 95%CI: 0.463-0.480). Sensitivity of clinical assessment of T and N stage ranged from 64.3% to 77.2% and 41.6% to 54.5%, respectively. Specificity ranged from 96.7% to 97.7% for T stage and 95.7% to 97.3% for N stage.

CONCLUSIONS

Clinical assessment of T and N stages of colon cancer had good diagnostic accuracy with moderate concordance with the final pathologic stage. While clinical assessment was highly specific with < 3% of patients being over-staged, it had modest sensitivity, especially for detection of nodal involvement. Diagnostic accuracy of clinical assessment of right and left colon cancers was similar, except for higher sensitivity and accuracy of assessment of nodal involvement in right than left colon cancers.

A clinical-radiomics nomogram based on spectral CT multi-parameter images for preoperative prediction of lymph node metastasis in colorectal cancer

To develop a clinical-radiomics nomogram based on spectral CT multi-parameter images for predicting lymph node metastasis in colorectal cancer. A total of 76 patients with colorectal cancer and 156 lymph nodes were included. The clinical data of the patients were collected, including gender, age, tumor location and size, preoperative tumor markers, etc. Three sets of conventional images in the arterial, venous, and delayed phases were obtained, and six sets of spectral images were reconstructed using the arterial phase spectral data, including virtual monoenergetic images (40 keV, 70 keV, 100 keV), iodine density maps, iodine no water maps, and virtual non-contrast images. Radiomics features of lymph nodes were extracted from the above images, respectively. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select features. A clinical model was constructed based on age and carcinoembryonic antigen (CEA) levels. The radiomics features selected were used to generate a composed radiomics signature (Com-RS). A nomogram was developed using age, CEA, and the Com-RS. The models' prediction efficiency, calibration, and clinical application value were evaluated by the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis, respectively. The nomogram outperforms the clinical model and the Com-RS (AUC = 0.879, 0.824). It is well calibrated and has great clinical application value. This study developed a clinical-radiomics nomogram based on spectral CT multi-parameter images, which can be used as an effective tool for preoperative personalized prediction of lymph node metastasis in colorectal cancer.

Sidedness and Molecular Pattern in Defining the Risk of Lymph Node Metastasis in Nonmetastatic Colorectal Cancer: Single-Center Retrospective Study

Background: Lymphadenectomy plays a central role in the treatment of localized colon cancer. While in left colon cancer the D3 lymphadenectomy/CME is considered the standard of care, lymphatic stations to be removed in right colon cancer are still a matter of discussion. The individuation of LNM risk factors could help in choosing the lymphadenectomy in right-sided tumors. This study aims to analyze the correlation of histopathological and molecular characteristics with lymph node metastasis, both in right- and left-sided colon cancer, and their impact on survival; Methods: We conducted a single-center observational retrospective study. The following data were collected and analyzed for each patient: demographics, histopathological and molecular data, and intraoperative and perioperative data. Statistical analyses were performed, including descriptive statistics, multivariate logistic regression and survival analysis; Results: An association between tumor size (pT, p < 0.001), grading (p = 0.013), budding (p < 0.001), LVI (79,4% p < 0.001) and LNM was observed. A multivariate analysis identified pT4 (OR 5.45, p < 0.001) and LVI+ (OR 10.7, p < 0.001) as significant predictors of LNM. Right-sided patients presented a worse OS when associated with LNM, while no significant difference was observed in N0 patients; Conclusions: histological and molecular analysis can help identify high risk patients, which could benefit from extended lymphadenectomies. These patients could be ideal candidates for the D3 lymphadenectomy/CME.

Correlating Ultrastructural Changes in the Invasion Area of Colorectal Cancer with CT and MRI Imaging

The cancer invasion of the large intestine, a destructive process that begins within the mucous membrane, causes cancer cells to gradually erode specific layers of the intestinal wall. The normal tissues of the intestine are progressively replaced by a tumour mass, leading to the impairment of the large intestine's proper morphology and function. At the ultrastructural level, the disintegration of the extracellular matrix (ECM) by cancer cells triggers the activation of inflammatory cells (macrophages) and connective tissue cells (myofibroblasts) in this area. This accumulation and the functional interactions between these cells form the tumour microenvironment (TM). The constant modulation of cancer cells and cancer-associated fibroblasts (CAFs) creates a specific milieu akin to non-healing wounds, which induces colon cancer cell proliferation and promotes their survival. This review focuses on the processes occurring at the "front of cancer invasion", with a particular focus on the role of the desmoplastic reaction in neoplasm development. It then correlates the findings from the microscopic observation of the cancer's ultrastructure with the potential of modern radiological imaging, such as computer tomography (CT) and magnetic resonance imaging (MRI), which visualizes the tumour, its boundaries, and the tissue reactions in the large intestine.

Neoadjuvant Chemotherapy in Colon Cancer: More Than Just an Optical Illusion

The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in Journal of Clinical Oncology, to patients seen in their own clinical practice.

Predictors of nodal positivity in clinically under-staged patients with colon cancer: A National Cancer Database study and proposal of a predictive scoring system

BACKGROUND

Colon cancer pathological and clinical staging may be disoncordant. This study assessed patients with colon cancer in whom the nodal status was clinically understaged.

METHODS

Patients with stage I-III clinical node-negative colon cancer from the National Cancer Database were included. Regression analyses were conducted to elucidate risk factors for clinical nodal understaging and a scoring system was developed to identify high-risk patients.

RESULTS

The study included 94,945 patients with 78.4 ​% of patients correctly staged and 21.6 ​% clinically understaged. The predictors of nodal positivity in clinically understaged patients were age <65 (OR 1.43), left-sided tumors (OR 1.41), elevated CEA (OR 2.03), moderately (OR 1.81) or poorly/undifferentiated tumors (OR 3.76), T1 tumors (OR 1.29), signet-ring cell histology (OR 2.26), and microsatellite-stable tumors (OR 1.4).

CONCLUSION

Patients with colon cancer and the above factors are more likely to have their nodal status clinically understaged. A scoring system has been developed to identify high-risk patients.

Deep-learning features based on F18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) to predict preoperative colorectal cancer lymph node metastasis

AIM

The objective of this study was to create and authenticate a prognostic model for lymph node metastasis (LNM) in colorectal cancer (CRC) that integrates clinical, radiomics, and deep transfer learning features.

MATERIALS AND METHODS

In this study, we analyzed data from 119 CRC patients who underwent F18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) scanning. The patient cohort was divided into training and validation subsets in an 8:2 ratio, with an additional 33 external data points for testing. Initially, we conducted univariate analysis to screen clinical parameters. Radiomics features were extracted from manually drawn images using pyradiomics, and deep-learning features, radiomics features, and clinical features were selected using Least Absolute Shrinkage and Selection Operator (LASSO) regression and Spearman correlation coefficient. We then constructed a model by training a support vector machine (SVM), and evaluated the performance of the prediction model by comparing the area under the curve (AUC), sensitivity, and specificity. Finally, we developed nomograms combining clinical and radiological features for interpretation and analysis.

RESULTS

The deep learning radiomics (DLR) nomogram model, which was developed by integrating deep learning, radiomics, and clinical features, exhibited excellent performance. The area under the curve was (AUC = 0.934, 95% confidence interval [CI]: 0.884-0.983) in the training cohort, (AUC = 0.902, 95% CI: 0.769-1.000) in the validation cohort, and (AUC = 0.836, 95% CI: 0.673-0.998) in the test cohort.

CONCLUSION

We developed a preoperative predictive machine-learning model using deep transfer learning, radiomics, and clinical features to differentiate LNM status in CRC, aiding in treatment decision-making for patients.

Performances of preoperative CT scan to predict the pTN stage for MSI/dMMR localized colon cancers

BACKGROUND

Neoadjuvant immunotherapy emerges as a promising strategy for patients with localized colon cancer (CC) harboring microsatellite instability/mismatch repair deficiency (MSI/dMMR). The aim of this study is to evaluate the concordance between clinical cTN stage assessed by preoperative computed tomography (CT) scan and pTN stage of MSI/dMMR CC.

PATIENTS AND METHODS

Consecutive patients diagnosed for localized MSI/dMMR CC and treated with upfront surgery between 2013 and 2022 in two French centers were eligible. Two independent radiologists, blinded to pathological findings, reviewed all preoperative CT scans and assessed cTN stage, with a third radiologist reviewing discordant cases. Radiological predictive diagnostic accuracy for pT4 and pN+ (N+ = N1 or N2) were calculated.

RESULTS

One hundred and thirteen patients were included (right CCs = 79%). CT scan diagnostic performances for pT4 were sensitivity (Se) = 33.3%; specificity (Sp) = 94.0%; positive predictive value (PPV) = 66.7%; and negative predictive value (NPV) = 79.6% and for pN+ were Se = 70.3%; Sp = 59.2%; PPV = 45.6%; and NPV = 80.4%. When pT-pN were combined, 37.5% of tumors identified as cT4 and/or cN+ were actually pT1-3 and pN0, and 23.1% of the pT4 and pN+ population was not identified as such radiologically.

CONCLUSION

The ability of preoperative CT scan to predict pT and pN stages is limited for localized MSI/dMMR CCs. Reassessing neoadjuvant strategies' benefit-risk balance in this population is needed.

Comparative evaluation of CT and MRI in the preoperative staging of colon cancer

The aim of this study is to compare the diagnostic performance of magnetic resonance imaging (MRI) against computed tomography (CT) in various aspects of local staging in colon cancer patients. This study was a prospective single arm diagnostic accuracy study. All consecutive adult patients with confirmed colon cancer that met the current criteria for surgical resection were considered as eligible. Diagnostic performance assessment included T (T1/T2 vs T3/T4 and < T3ab vs > T3cd) and N (N positive) staging, serosa and retroperitoneal surgical margin (RSM) involvement and extramural vascular invasion (EMVI). Imaging was based on a 3 Tesla MRI system and the evaluation of all sequences (T1, T2 and diffusion-weighted imaging-DWI series) by two independent readers. CT scan was performed in a 128 row multidetector (MD) CT scanner (slice thickness: 1 mm) with intravenous contrast. Pathology report was considered as the gold standard for local staging. Sensitivity (SE), specificity (SP), and area under the curve (AUC) were calculated for both observers. MRI displayed a higher diagnostic performance over CT in terms of T1/T2 vs T3/T4 (SE: 100% vs 83.9%, SP: 96.6% vs 81%, AUC: 0.825 vs 0.983, p < 0.001), N positive (p < 0.001) and EMVI (p = 0.023) assessment. An excellent performance of MRI was noted in the T3ab vs T3cd (CT AUCReader1: 0.636, AUCReader2: 0.55 vs MRI AUCReader1: 0.829 AUCReader2 0.846, p = 0.01) and RSM invasion diagnosis. In contrast to these, MRI did not perform well in the identification of serosa invasion. MRI had a higher diagnostic yield than CT in several local staging parameters.

Characteristics and outcomes of large (≥5 cm) colonic adenocarcinomas and comparing outcomes of minimally invasive and open surgery for stage I to III disease

BACKGROUND

Colon cancer prognosis is primarily dependent on the stage at diagnosis, but tumor size and location may also impact prognosis. This study aimed to assess the characteristics and outcomes of patients with ≥5 cm colonic adenocarcinomas and compare outcomes of open and minimally invasive surgery for stage I to III large colonic adenocarcinomas.

METHODS

The National Cancer Database (2010-2019) was searched for patients with colonic adenocarcinomas ≥5 cm. Outcomes of patients who underwent minimally invasive surgery or open surgery were compared after propensity-score matching. The primary outcome was 5-year overall survival and, secondarily, hospital stay, surgical margins, and short-term mortality.

RESULTS

A total of 126,959 patients were included (22.1% of all diagnosed adenocarcinomas). 56% of tumors were right-sided, 32.6% were left-sided, and 11.4% were in the transverse colon. Stage IV disease was recorded in 34.6% of patients. Lymphovascular invasion, perineural invasion, and Kirsten rat sarcoma viral oncogene homolog mutations were recorded in 35.7%, 14.9%, and 41.6% of patients. The rate of positive surgical margins was 9.8%. Median hospital stay was 6 (interquartile range: 4-8) days. 30- and 90-day mortality rates were 4.1% and 7.5%, respectively. After matching, 15,228 patients in the open surgery group were matched to a similar number in the minimally invasive surgery group. The minimally invasive surgery group was associated with significantly lower rates of 30- and 90-day mortality, positive surgical margins, shorter hospital stay, and longer median overall survival (110.6 vs 86.6 months, P < .001) than did open surgery.

CONCLUSION

Large colonic adenocarcinomas are mostly right-sided or transverse and present at a more advanced stage with adverse pathologic features. Minimally invasive surgery was associated with better overall survival and short-term benefits when compared with open surgery.

Non-operative management after immune checkpoint inhibitors for early-stage, dMMR/MSI-H gastrointestinal cancers

Surgery is a standard treatment for early-stage gastrointestinal cancers, often preceded by neoadjuvant chemo(radio)therapy or followed by adjuvant therapy. While leading to cure in a proportion of patients, it has some drawbacks such as intra/post-operative complications, mutilation and life-long functional sequelae. Further to the unprecedented efficacy data from studies of immune checkpoint inhibitors for advanced mismatch repair deficient/microsatellite instable (dMMR/MSI-H) tumours, a strong interest has recently emerged for the investigation of such agents in the neoadjuvant setting. Although limited by the exploratory design and small sample size, trials of neoadjuvant immune checkpoint inhibitors for early-stage dMMR/MSI-H gastrointestinal cancers have consistently reported complete response rates ranging from 70 % to 100 %. As a result, the question has arisen as to whether surgery is still needed or organ-preserving strategies should be offered to this especially immuno-sensitive population. In this article, we discuss the available evidence for neoadjuvant immune checkpoint inhibitors in dMMR/MSI-H gastrointestinal cancers and analyse opportunities and challenges to the implementation of non-operative management approaches in this setting.

Imaging in the era of risk-adapted treatment in colon cancer

The treatment landscape for patients with colon cancer is continuously evolving. Risk-adapted treatment strategies, including neoadjuvant chemotherapy and immunotherapy, are slowly finding their way into clinical practice and guidelines. Radiologists are pivotal in guiding clinicians toward the most optimal treatment for each colon cancer patient. This review provides an overview of recent and upcoming advances in the diagnostic management of colon cancer and the radiologist's role in the multidisciplinary approach to treating colon cancer.

2-[18F]FDG PET-based quantification of lymph node metabolic heterogeneity for predicting lymph node metastasis in patients with colorectal cancer

BACKGROUND AND PURPOSE

The pre-surgical estimation of lymph node (LN) metastasis in colorectal cancer (CRC) poses a significant diagnostic predicament. The associations between LN morphology, density, and metabolic heterogeneity and LN metastasis status in CRCs have been seldomly examined through the lens of radiomics. This research aimed to assess 2-[18F]FDG PET-based quantification of intratumoral metabolic heterogeneity for predicting lymph node metastasis in patients with colorectal cancer.

MATERIALS AND METHODS

The construction of the model utilized data from 264 CRC patients, all of whom underwent preoperative 2-[18F]FDG PET/CT. Radiomic features were extracted from PET and CT images of LNs. Least absolute shrinkage and selection operator (LASSO) regression was implemented for selecting pertinent imaging features with a tenfold cross-validation. The predictive accuracy for LN metastasis status was juxtaposed against traditional methodologies (comprising CT-reported LN status and PET/CT-reported LN status) by deploying the receiver operating characteristic (ROC) curve analysis. The radiomics signature was evaluated based on discrimination, calibration, and clinical utility parameters. The model was further subjected to validation using an independent cohort of 132 patients from the period of January 2012 to June 2020.

RESULTS

The radiomics model was composed of eight significant radiomic features (five from PET and three from CT), encapsulating metabolic and density heterogeneity. The radiomics signature (area under the curve (AUC), 0.908) showcased a significantly superior performance compared to CT-reported LN status (AUC, 0.563, P < 0.001) and PET/CT-reported LN status (AUC, 0.64, P < 0.001) for predicting LN-positive or LN-negative status. The radiomics signature (AUC, 0.885) also showcased a significantly superior performance compared to CT-reported LN status (AUC, 0.587, P < 0.001) and PET/CT-reported LN status (AUC, 0.621, P < 0.001) to identify N1 and N2. This signature maintained its independence from clinical risk factors and exhibited robustness in the validation test set. Decision curve analysis attested to the clinical utility of the radiomics signature.

CONCLUSIONS

The radiomics signature based on 2-[18F]FDG PET/CT, which derived image features directly from LNs irrespective of clinical risk factors, displayed enhanced diagnostic performance compared to conventional CT or PET/CT-reported LN status. This allows for the identification of pre-surgical LN metastasis status and facilitates a patient-specific prediction of LN metastasis status in CRC patients.

The Additional Role of F18-FDG PET/CT in Characterizing MRI-Diagnosed Tumor Deposits in Locally Advanced Rectal Cancer

Rationale: F18-FDG PET/CT may be helpful in baseline staging of patients with high-risk LARC presenting with vascular tumor deposits (TDs), in addition to standard pelvic MRI and CT staging. Methods: All patients with locally advanced rectal cancer that had TDs on their baseline MRI of the pelvis and had a baseline F18-FDG PET/CT between May 2016 and December 2020 were included in this retrospective study. TDs as well as lymph nodes identified on pelvic MRI were correlated to the corresponding nodular structures on a standard F18-FDG PET/CT, including measurements of nodular SUVmax and SUVmean. In addition, the effects of partial volume and spill-in on SUV measurements were studied. Results: A total number of 62 patients were included, in which 198 TDs were identified as well as 106 lymph nodes (both normal and metastatic). After ruling out partial volume effects and spill-in, 23 nodular structures remained that allowed for reliable measurement of SUVmax: 19 TDs and 4 LNs. The median SUVmax between TDs and LNs was not significantly different (p = 0.096): 4.6 (range 0.8 to 11.3) versus 2.8 (range 1.9 to 3.9). For the median SUVmean, there was a trend towards a significant difference (p = 0.08): 3.9 (range 0.7 to 7.8) versus 2.3 (range 1.5 to 3.4). Most nodular structures showing either an SUVmax or SUVmean ≥ 4 were characterized as TDs on MRI, while only two were characterized as LNs. Conclusions: SUV measurements may help in separating TDs from lymph node metastases or normal lymph nodes in patients with high-risk LARC.

It Is What the Surgeon Does Not See That Kills the Patient

BACKGROUND

Patients with colon cancer may present at multiple different stages of the disease process. Many patients can be cured of colon cancer as a result of a simple surgical procedure usually performed by minimally invasive techniques. However, there are a variable number of patients, estimated at approximately 10%, who have a more advanced disease. If these patients are treated by the current conventional standard of care, the likelihood for treatment failure is extremely high.

METHODS

These are not patients with known disseminated disease but patients who are at high risk of recurrent disease unless special treatments are initiated preoperatively and intraoperatively. The identification of these patients is by (1) a high-quality CT scan, (2) tumor markers found preoperatively, (3) colonoscopic findings, and (4) symptoms.

RESULTS

Patients identified as being at high risk require special preoperative treatments which include neoadjuvant chemotherapy. Intraoperative chemotherapy with HIPEC should occur as part of the treatment if peritoneal metastases are documented by biopsy. In the operating room, a thorough exploration of all possible occult peritoneal spaces for metastatic disease needs to be performed. A modified cytoreductive surgical procedure along with a colon resection is performed in order to minimize sites of occult peritoneal metastases. This includes the greater omentum, ovaries, and tubes in postmenopausal women. Peritonectomy is used to create a shroud around the tumor so that all peritoneum that has been in direct contact with the tumor surface is resected and is used as a barrier against tumor cell dissemination in the process of colon cancer resection. If peritoneal metastases are visualized at any site, HIPEC should be included as part of the treatment package.

CONCLUSIONS

I am convinced that patients at high risk of recurrence will have an improved outcome with proper preoperative evaluation, preoperative neoadjuvant chemotherapy, and a revised intraoperative management strategy.

Effect of complete mesocolic excision (cme) on long-term survival after right colectomy for cancer: multivariate meta-analysis and restricted mean survival time estimation

INTRODUCTION

Debate exists concerning the impact of complete mesocolic excision (CME) on long-term oncological outcomes. The aim of this review was to condense the updated literature and assess the effect of CME on long-term survival after right colectomy for cancer.

METHODS

PubMed, MEDLINE, Scopus, and Web of Science were searched through July 2023. The included studies evaluated the effect of CME on survival. The primary outcome was long-term overall survival. Restricted mean survival time difference (RMSTD), hazard ratio (HR), and 95% confidence intervals (CI) were used as pooled effect size measures. GRADE methodology was used to summarize the certainty of evidence.

RESULTS

Ten studies (3665 patients) were included. Overall, 1443 (39.4%) underwent CME. The RMSTD analysis shows that at 60-month follow-up, stage I-III CME patients lived 2.5 months (95% CI 1.1-4.1) more on average compared with noCME patients. Similarly, stage III patients that underwent CME lived longer compared to noCME patients at 55-month follow-up (6.1 months; 95% CI 3.4-8.5). The time-dependent HRs analysis for CME vs. noCME (stage I-III disease) shows a higher mortality hazard in patients with noCME at 6 months (HR 0.46, 95% CI 0.29-0.71), 12 months (HR 0.57, 95% CI 0.43-0.73), and 24 months (HR 0.73, 95% CI 0.57-0.92) up to 27 months.

CONCLUSIONS

This study suggests that CME is associated with unclear OS benefit in stage I-III disease. Caution is recommended to avoid overestimation of the effect of CME in stage III disease since the marginal benefit of a more extended resection may have been influenced by tumor biology/molecular profile and multimodal adjuvant treatments.

Preoperative assessment of grade, T stage, and lymph node involvement: machine learning-based CT texture analysis in colon cancer

PURPOSE

To investigate whether texture analysis of primary colonic mass in preoperative abdominal computed tomography (CT) scans of patients diagnosed with colon cancer could predict tumor grade, T stage, and lymph node involvement using machine learning (ML) algorithms.

MATERIALS AND METHODS

This retrospective study included 73 patients diagnosed with colon cancer. Texture features were extracted from contrast-enhanced CT images using LifeX software. First, feature reduction was performed by two radiologists through reproducibility analysis. Using the analysis of variance method, the parameters that best predicted lymph node involvement, grade, and T stage were determined. The predictive performance of these parameters was assessed using Orange software with the k-nearest neighbor (kNN), random forest, gradient boosting, and neural network models, and their area under the curve values were calculated.

RESULTS

There was excellent reproducibility between the two radiologists in terms of 49 of the 58 texture parameters that were subsequently subject to further analysis. Considering all four ML algorithms, the mean AUC and accuracy ranges were 0.557-0.800 and 47-76%, respectively, for the prediction of lymph node involvement; 0.666-0.846 and 68-77%, respectively, for the prediction of grade; and 0.768-0.962 and 81-88%, respectively, for the prediction of T stage. The best performance was achieved with the random forest model in the prediction of LN involvement, the kNN model for the prediction of grade, and the gradient boosting model for the prediction of T stage.

CONCLUSION

The results of this study suggest that the texture analysis of preoperative CT scans obtained for staging purposes in colon cancer can predict the presence of advanced-stage tumors, high tumor grade, and lymph node involvement with moderate specificity and sensitivity rates when evaluated using ML models.

Complete mesocolic excision for colon cancer: current status and controversies

According to Hohenberger's original description, complete mesocolic excision for colon cancer involves precise dissection of the avascular embryonic plane between the parietal retroperitoneum and visceral peritoneum of the mesocolon. This ensures mesocolic integrity, access to high ligation of the supplying vessels at their origin and an associated extended lymphadenectomy. Results from centres which have adopted this approach routinely have demonstrated that oncological outcomes can be improved by the rigorous implementation of established principles of cancer surgery. Meticulous anatomical dissection along embryonic planes is a well-established principle of precision cancer surgery used routinely by the specialist colorectal surgeon. Therefore, the real question concerns the need for true central vascular ligation and associated extended (D3) lymphadenectomy or otherwise, particularly along the superior mesenteric vessels when performing a right colectomy. Whether this approach results in improved overall or disease-free survival remains unclear and its role remains controversial particularly given the potential for significant morbidity associated with a more extensive central vascular dissection. Current literature is limited by considerable bias, as well as inconsistent and variable terminology, and the results of established randomized trials are awaited. As a result of the current state of equipoise, various national guidelines have disparate recommendations as to when complete mesocolic excision should be performed if at all. This article aims to review the rationale for and technical aspects of complete mesocolic excision, summarize available short and long term outcome data and address current controversies.

Enzymatic Fat Dissolution Improves Detection of Small Lymph Nodes in Colon Cancer Surgery

Background Accurate lymph node evaluation is essential for staging colon cancer and guiding postoperative treatment decisions. In this study, we compared the efficacy of a simple enzymatic fat dissolution method with the conventional method for lymph node sampling from specimens after colon cancer surgery. Methods We enrolled 58 patients who underwent elective laparoscopic surgery for colon adenocarcinoma between May 2018 and May 2021 at Fukuoka University Hospital in Fukuoka, Japan. The specimens from these patients were treated using fat dissolution and were compared with specimens from 58 patients for which conventional manual palpation was used. Results A significantly greater number of lymph nodes were detected by the fat dissolution method compared with the conventional method (average per patient, 27.5 vs. 22.6, P = 0.02). In particular, the between-group difference was significant for lymph nodes measuring <5 mm (average per patient, 26.1 vs. 20.9; P = 0.01). Multivariate analysis showed that, compared with the conventional method, the fat dissolution method was significantly associated with the identification of lymph node metastasis. The positive rate of lymph nodes ≥10 mm in diameter was markedly higher along the inferior mesenteric artery than the ileocolic artery (100% vs. 52.6%). Conclusions The use of the fat dissolution method led to an increase in the number of small lymph nodes detected. Rates of metastasis according to lymph node size may depend on the lymph node station.

Complete mesocolic excision and extended lymphadenectomy: Where should we stand?

Debate regarding the risks and merits of complete mesocolic excision and extended lymphadenectomy is ongoing, particularly for right-sided colon cancers. In this article, we hope to provide a succinct yet encompassing review of the relevant literature. We posit that complete mesocolic excision with D3 dissection is indicated in select patients with colon cancers, particularly those distal to the cecum.

Deep learning to predict lymph node status on pre-operative staging CT in patients with colon cancer

INTRODUCTION

Lymph node (LN) metastases are an important determinant of survival in patients with colon cancer, but remain difficult to accurately diagnose on preoperative imaging. This study aimed to develop and evaluate a deep learning model to predict LN status on preoperative staging CT.

METHODS

In this ambispective diagnostic study, a deep learning model using a ResNet-50 framework was developed to predict LN status based on preoperative staging CT. Patients with a preoperative staging abdominopelvic CT who underwent surgical resection for colon cancer were enrolled. Data were retrospectively collected from February 2007 to October 2019 and randomly separated into training, validation, and testing cohort 1. To prospectively test the deep learning model, data for testing cohort 2 was collected from October 2019 to July 2021. Diagnostic performance measures were assessed by the AUROC.

RESULTS

A total of 1,201 patients (median [range] age, 72 [28-98 years]; 653 [54.4%] male) fulfilled the eligibility criteria and were included in the training (n = 401), validation (n = 100), testing cohort 1 (n = 500) and testing cohort 2 (n = 200). The deep learning model achieved an AUROC of 0.619 (95% CI 0.507-0.731) in the validation cohort. In testing cohort 1 and testing cohort 2, the AUROC was 0.542 (95% CI 0.489-0.595) and 0.486 (95% CI 0.403-0.568), respectively.

CONCLUSION

A deep learning model based on a ResNet-50 framework does not predict LN status on preoperative staging CT in patients with colon cancer.

The diagnostic accuracy of local staging in colon cancer based on computed tomography (CT): evaluating the role of extramural venous invasion and tumour deposits

PURPOSE

The shift from adjuvant to neoadjuvant treatment in colon cancer demands the radiological selection of patients for systemic therapy. The aim of this study was to evaluate the accuracy of the CT-based TNM stage and high-risk features, including extramural venous invasion (EMVI) and tumour deposits, in the identification of patients with histopathological advanced disease, currently considered for neoadjuvant treatment (T3-4 disease).

METHODS

All consecutive patients surgically treated for non-metastatic colon cancer between January 2018 and January 2020 in a referral centre for colorectal cancer were identified retrospectively. All tumours were staged on CT according to the TNM classification system. Additionally, the presence of EMVI and tumour deposits on CT was evaluated. The histopathological TNM classification was used as reference standard.

RESULTS

A total of 176 patients were included. Histopathological T3-4 colon cancer was present in 85.0% of the patients with CT-detected T3-4 disease. Histopathological T3-4 colon cancer was present in 96.4% of the patients with CT-detected T3-4 colon cancer in the presence of both CT-detected EMVI and CT-detected tumour deposits. Histopathological T0-2 colon cancer was present in 50.8% of the patients with CT-detected T0-2 disease, and in 32.4% of the patients without CT-detected EMVI and tumour deposits.

CONCLUSION

The diagnostic accuracy of CT-based staging was comparable with previous studies. The presence of high-risk features on CT increased the probability of histopathological T3-4 colon cancer. However, a substantial part of the patients without CT-detected EMVI and tumour deposits was diagnosed with histopathological T3-4 disease. Hence, more accurate selection criteria are required to correctly identify patients with locally advanced disease.

A Review on Emerging Techniques for Diagnosis of Colorectal Cancer

Common detection methods in practice for diagnosing colorectal cancer (CRC) are painful and invasive leading to less participation of individuals for CRC diagnosis. Whereas, improved or enhanced imaging systems and other minimally invasive techniques with shorter detection times deliver greater detail and less discomfort in individuals. Thus, this review is a summary of the diagnostic tests, ranging from the simple potential use in developing a flexible CRC treatment to the patient's potential benefits in receiving less invasive procedures and the advanced treatments that might provide a better assessment for the diagnosis of CRC and reduce the mortality related to CRC.

Neoadjuvant chemotherapy for early-stage colon cancer

Surgery with or without adjuvant chemotherapy is the standard treatment for early-stage colon cancer. However, evidence has recently emerged for neoadjuvant chemotherapy, with the results of randomised clinical trials sparking debates within multidisciplinary teams and splitting the gastrointestinal oncology community. Further to a systematic search of the literature, we provide a thorough and in-depth analysis of the findings from these trials, highlighting the advantages and disadvantages of neoadjuvant chemotherapy. We conclude that, while there is a potential value of moving systemic therapy from the post-operative to the pre-operative setting, the available evidence does not justify a shift in the treatment paradigm of early-stage colon cancer, and surgery with or without adjuvant chemotherapy should remain the standard approach for these patients.

Prognostic impact of extramural venous invasion detected by contrast-enhanced CT colonography in colon cancer

BACKGROUND

The impact of computed tomography (CT)-detected extramural venous invasion on the recurrence of colon cancer is not fully understood. The aim of this study was to investigate the clinical significance of extramural venous invasion diagnosed before surgery by contrast-enhanced CT colonography using three-dimensional multiplanar reconstruction images.

METHODS

Patients with colon cancer staged greater than or equal to T2 and/or stage I-III who underwent contrast-enhanced CT colonography between 2013 and 2018 at the National Cancer Center Hospital in Japan were retrospectively investigated for CT-detected extramural venous invasion. Inter-observer agreement for the detection of CT-detected extramural venous invasion was evaluated and Kaplan-Meier survival curves were plotted for recurrence-free survival using CT-TNM staging and CT-detected extramural venous invasion. Preoperative clinical variables were analysed using Cox regression for recurrence-free survival.

RESULTS

Out of 922 eligible patients, 544 cases were analysed (50 (9.2 per cent) were diagnosed as positive for CT-detected extramural venous invasion and 494 (90.8 per cent) were diagnosed as negative for CT-detected extramural venous invasion). The inter-observer agreement for CT-detected extramural venous invasion had a κ coefficient of 0.830. The group positive for CT-detected extramural venous invasion had a median follow-up of 62.1 months, whereas the group negative for CT-detected extramural venous invasion had a median follow-up of 60.7 months. When CT-TNM stage was stratified according to CT-detected extramural venous invasion status, CT-T3 N(-)extramural venous invasion(+) had a poor prognosis compared with CT-T3 N(-)extramural venous invasion(-) and CT-stage I (5-year recurrence-free survival of 50.6 versus 89.3 and 90.1 per cent respectively; P < 0.001). In CT-stage III, the group positive for CT-detected extramural venous invasion also had a poor prognosis compared with the group negative for CT-detected extramural venous invasion (5-year recurrence-free survival of 52.0 versus 78.5 per cent respectively; P = 0.003). Multivariable analysis revealed that recurrence was associated with CT-T4 (HR 3.10, 95 per cent c.i. 1.85 to 5.20; P < 0.001) and CT-detected extramural venous invasion (HR 3.08, 95 per cent c.i. 1.90 to 5.00; P < 0.001).

CONCLUSION

CT-detected extramural venous invasion was found to be an independent predictor of recurrence and could be used in combination with preoperative TNM staging to identify patients at high risk of recurrence.

CT Colonography Reporting and Data System (C-RADS): Version 2023 Update

The CT Colonography Reporting and Data System (C-RADS) has withstood the test of time and proven to be a robust classification scheme for CT colonography (CTC) findings. C-RADS version 2023 represents an update on the scheme used for colorectal and extracolonic findings at CTC. The update provides useful insights gained since the implementation of the original system in 2005. Increased experience has demonstrated confusion on how to classify the mass-like appearance of the colon consisting of soft tissue attenuation that occurs in segments with acute or chronic diverticulitis. Therefore, the update introduces a new subcategory, C2b, specifically for mass-like diverticular strictures, which are likely benign. Additionally, the update simplifies extracolonic classification by combining E1 and E2 categories into an updated extracolonic category of E1/E2 since, irrespective of whether a finding is considered a normal variant (category E1) or an otherwise clinically unimportant finding (category E2), no additional follow-up is required. This simplifies and streamlines the classification into one category, which results in the same management recommendation.

Accuracy of pre-operative 18-fluoride fluorodeoxyglucose positron emission tomography (FDG-PET) in predicting lymph node involvement in colon cancer

BACKGROUND

Accurate staging of colon cancer is imperative in directing treatment and prognostication. Existing literature on pre-operative accuracy of FDG-PET/CT in detecting lymph node disease often combines colon and rectal cancer, examines rectal cancers alone, and rarely assesses colon cancer in isolation. Our aim was to assess pre-operative utility of FDG-PET/CT in detecting lymph node disease in colon cancer.

METHODS

A retrospective cohort analysis was performed at a single Australian institution between 2017 and 2022 to identify treatment naive primary colonic tumours. Primary outcome was sensitivity and specificity using formal surgical histopathology as gold standard. Secondary outcomes were patient and tumour factors predictive of FDG-PET/CT positive disease including pre-operative CEA, mismatch repair status, duration to surgery, and tumour T-stage.

RESULTS

Three hundred and thirty-nine patients were identified. Thirty-four had pre-operative FDG-PET/CT without neoadjuvant therapy. The mean surgical lymph node harvest was 18 nodes. Twenty-five patients had moderately differentiated tumours. The median duration between FDG-PET/CT and operation was 17 days. Pre-operative FDG-PET/CT suggested positive lymph node involvement in 12 patients. Compared to final lymph node histopathology, FDG-PET/CT had a sensitivity of 53%, specificity of 82%, positive predictive value of 75%, negative predictive value of 64% and accuracy of 68%. There was no significant difference between groups for secondary outcomes.

CONCLUSION

FDG-PET/CT has moderate specificity but poor sensitivity in the detection of lymph node involvement in colon cancer. Its utility should likely remain isolated to investigating equivocal lesions or follow up of known PET avid disease.

Endoscopic and imaging outcomes of PD-1 therapy in localised dMMR colorectal cancer

BACKGROUND

Neoadjuvant immune checkpoint blockade (IO) is emerging as a therapeutic option for patients with deficient mismatch repair (dMMR) colorectal cancer (CRC) given high pathological response rates. The aim of the study was to characterise imaging and endoscopic response to IO.

METHODS

A retrospective analysis of patients with localised dMMR CRC that received at least one cycle of neoadjuvant anti-PD-1 therapy was conducted. Endoscopy, imaging, and pathological outcomes were reviewed to determine response to treatment according to standardised criteria.

RESULTS

Thirty-eight patients had received IO for the treatment of localised CRC (median eight cycles). Among evaluable cases (n = 31 for endoscopy and n = 34 for imaging), the best endoscopic response was complete response (CR) in 45% of cases, and the best radiographic response was CR in 23% of cases. Imaging CR rate after ≤4 cycles of IO (n = 1) was 6% compared to 44% after >4 IO cycles (n = 7). Among 28 patients with imaging and endoscopy available, a discrepancy in best response was noted in 15 (54%) cases. At a median follow-up of 28.2 months from IO start, 18 patients underwent surgical resection of which 11 (61%) had pathological CR (pCR). Despite pCR or no evidence of progression ≥6 months after completion of IO among non-operatively managed patients, 72% and 42% of patients had non-CR on imaging and endoscopy, respectively.

CONCLUSIONS

Discrepancies between imaging and endoscopy are prevalent, and irregularities identified on these modalities can be identified despite pathological remission. Improved clinical response criteria are warranted.

Diagnostic accuracy of CT for local staging of colon cancer: A nationwide study in the Netherlands

OBJECTIVE

To determine the accuracy of computed tomography (CT)-based staging in selecting high-risk colon cancer patients who would benefit from neoadjuvant chemotherapy while avoiding overtreatment.

METHODS

Data of adult patients diagnosed with non-metastatic primary colon cancer in 2005-2020, who underwent surgical resection without neoadjuvant chemotherapy, were retrospectively collected from the Netherlands Cancer Registry. Agreement between clinical and pathological evaluation for each T and N stage was calculated. Sensitivity and specificity analyses were conducted to predict T3-T4 and N1-N2 stages, with histopathology as the reference standard.

RESULTS

Data from 44,471 patients (median age, 71 years, 50% female) were evaluated. We included 38,915 patients with complete T stage and 39,565 patients with complete N stage for analyses. The overall clinical-pathological agreement for T stage was 59% and for N stage 57%. The sensitivity and specificity of CT to detect T3-T4 tumours were 80% (95% confidence interval (CI): 0.79, 0.80) and 76% (95% CI: 0.75, 0.77), respectively, with a positive predictive value (PPV) of 92% (95% CI: 0.92, 0.92). The sensitivity and specificity of CT to detect N1-N2 category were 62% (95% CI: 0.61, 0.63) and 70% (95% CI: 0.69, 0.71), respectively, with PPV 60% (95% CI: 0.59, 0.60).

CONCLUSION

CT-based staging shows limited accuracy in selecting colon cancer patients who would benefit from neoadjuvant therapy without risking overtreatment. Detection of lymph node metastases with CT remains unreliable.

Effect of visceral fat area on the accuracy of preoperative CT-N staging of colorectal cancer

OBJECTIVE

To investigate the effect of visceral fat area (VFA) on the accuracy of preoperative CT-N staging of colorectal cancer.

METHODS

We retrospectively reviewed the clinical and imaging data of 385 CRC patients who underwent surgical resection for colorectal cancer between January 2018 and July 2021. Preoperative CT-N staging and imaging features were determined independently by two radiologists. Using postoperative pathology as the gold standard, patients were divided into accurately and incorrectly staged groups, and clinical and imaging characteristics were compared between the two groups. VFA and subcutaneous fat area (SFA) at the L3 vertebral level, sex, age, BMI, tumor location, size, and tumor circumference ratio (TCR) were included. Logistic regression analysis was used to evaluate the independent factors influencing the accuracy of preoperative N staging of colorectal cancer.

RESULTS

Of the 385 patients enrolled, 259 (67.27%) were in the preoperative N-stage accurate staging group, and 126 (32.73%) were in the incorrectly staged group. Univariate analysis showed that there were significant differences in BMI, tumor location, VFA, SFA, size and TCR between the two groups (P<0.05). Logistic regression analysis showed that VFA (95% CI: 1.277, 3.813; P=0.005) and TCR (95% CI: 1.649, 17.545; P=0.005) were independent factors affecting the accuracy of N staging. The optimal cutoff points for VFA and TCR in predicting incorrect staging were 110 cm2 and 0.675, respectively.

CONCLUSIONS

Colorectal cancer patients with lower VFA and higher TCR and preoperative CT-N staging had an increased risk for diagnostic errors.

Diagnostic Accuracy of Abdominal CT for Locally Advanced Colon Tumors: Can We Really Entrust Certain Decisions to the Reliability of CT?

Many different options of neoadjuvant treatments for advanced colon cancer are emerging. An accurate preoperative staging is crucial to select the most appropriate treatment option. A retrospective study was carried out on a national series of operated patients with T4 tumors. Considering the anatomo-pathological analysis of the surgical specimen as the gold standard, a diagnostic accuracy study was carried out on the variables T and N staging and the presence of peritoneal metastases (M1c). The parameters calculated were sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios, as well as the overall accuracy. A total of 50 centers participated in the study in which 1950 patients were analyzed. The sensitivity of CT for correct staging of T4 colon tumors was 57%. Regarding N staging, the overall accuracy was 63%, with a sensitivity of 64% and a specificity of 62%; however, the positive and negative likelihood ratios were 1.7 and 0.58, respectively. For the diagnosis of peritoneal metastases, the accuracy was 94.8%, with a sensitivity of 40% and specificity of 98%; in the case of peritoneal metastases, the positive and negative likelihood ratios were 24.4 and 0.61, respectively. The diagnostic accuracy of CT in the setting of advanced colon cancer still has some shortcomings for accurate diagnosis of stage T4, correct classification of lymph nodes, and preoperative detection of peritoneal metastases.

Nationwide practice in CT-based preoperative staging of colon cancer and concordance with definitive pathology

INTRODUCTION

In an era of exploring patient-tailored treatment options for colon cancer, preoperative staging is increasingly important. This study aimed to evaluate completeness and reliability of CT-based preoperative locoregional colon cancer staging in Dutch hospitals.

MATERIALS AND METHODS

Patients who underwent elective oncological resection of colon cancer without neoadjuvant treatment in 77 Dutch hospitals were evaluated between 2011 and 2021. Completeness of T-stage was calculated for individual hospitals and stratified based on a 60% cut-off. Concordance between routine CT-based preoperative locoregional staging (cTN) and definitive pathological staging (pTN) was examined.

RESULTS

A total of 59,558 patients were included with an average completeness of 43.4% and 53.4% for T and N-stage, respectively. Completeness of T-stage improved from 4.9% in 2011-2014 to 74.4% in 2019-2021. Median completeness for individual hospitals was 53.9% (IQR 27.3-80.5%) and were not significantly different between low and high-volume hospitals. Sensitivity and specificity for T3-4 tumours were relatively low: 75.1% and 76.0%, respectively. cT1-2 tumours were frequently understaged based on a low negative predictive value of 56.8%. Distinction of cT4 and cN2 disease had a high specificity (>95%), but a very low sensitivity (<50%). Positive predictive values of <60% indicated that cT4 and cN1-2 were often overstaged. Completeness and time period did not influence reliability of staging.

CONCLUSION

Completeness of locoregional staging of colon cancer improved during recent years and varied between hospitals independently from case volume. Discriminating cT1-2 from cT3-4 tumours resulted in substantial understaging and overstaging, additionally cT4 and cN1-2 were overstaged in >40% of cases.

CT morphological features for predicting the risk of lymph node metastasis in T1 colorectal cancer

OBJECTIVES

The aim of this study is to evaluate the feasibility of clinicopathological characteristics and computed tomography (CT) morphological features in predicting lymph node metastasis (LNM) for patients with T1 colorectal cancer (CRC).

METHODS

A total of 144 patients with T1 CRC who underwent CT scans and surgical resection were retrospectively included in our study. The clinicopathological characteristics and CT morphological features were assessed by two observers. Univariate and multiple logistic regression analyses were used to identify significant LNM predictive variables. Then a model was developed using the independent predictive factors. The predictive model was subjected to bootstrapping validation (1000 bootstrap resamples) to calculate the calibration curve and relative C-index.

RESULTS

LNM were found in 30/144 patients (20.83%). Four independent risk factors were determined in the multiple logistic regression analysis, including presence of necrosis (adjusted odds ratio [OR] = 10.32, 95% confidence interval [CI] 1.96-54.3, p = 0.004), irregular outer border (adjusted OR = 5.94, 95% CI 1.39-25.45, p = 0.035), and heterogeneity enhancement (adjusted OR = 7.35, 95% CI 3.11-17.38, p = 0.007), as well as tumor location (adjusted ORright-sided colon = 0.05 [0.01-0.60], p = 0.018; adjusted ORrectum = 0.22 [0.06-0.83], p = 0.026). In the internal validation cohort, the model showed good calibration and good discrimination with a C-index of 0.89.

CONCLUSIONS

There are significant associations between lymphatic metastasis status and tumor location as well as CT morphologic features in T1 CRC, which could help the doctor make decisions for additional surgery after endoscopic resection.

KEY POINTS

• LNM more frequently occurs in left-sided T1 colon cancer than in right-sided T1 colon and rectal cancer. • CT morphologic features are risk factors for LNM of T1 CRC, which may be related to fundamental biological behaviors. • The combination of tumor location and CT morphologic features can more effectively assist in predicting LNM in patients with T1 CRC, and decrease the rate of unnecessary extra surgeries after endoscopic resection.

The impact of mismatch repair status and systemic inflammatory markers on radiological staging in colon cancer

OBJECTIVE

Mismatch repair (MMR) deficient (dMMR) colon cancer (CC) is distinct from MMR proficient (pMMR) CC, yet the impact of MMR status on radiological staging is unclear. The purpose of this study was to investigate how MMR status impacts CC CT staging.

METHODS

We retrospectively compared CT staging accuracy between dMMR and pMMR CC patients undergoing curative resection. Accuracy was assessed as individual tumour (T)/nodal (N) stages and as dichotomous "statuses" (T1/2 vs T3/4; N0 vs N1/2). Patient characteristics were analysed for factors to support staging.

RESULTS

There was no significant difference in overall staging accuracy between the dMMR (44 patients) and pMMR (57 patients) groups. dMMR tumours with incorrect N stage/"status" were more likely to be overstaged than pMMR tumours (90% vs 59%; p = 0.023 for "N status"). Platelet count, CRP and neutrophil count (AUC 0.76 (p = 0.0078), 0.75 (p = 0.034) and 0.70 (p = 0.044), respectively) were associated with "N status" in dMMR tumours.

CONCLUSION

Whilst overall staging accuracy was similar between groups, incorrectly N staged dMMR tumours were more likely to be overstaged than pMMR tumours, risking inappropriate surgical or neoadjuvant treatment. We describe novel relationships between several inflammatory markers and pathological "N status" in dMMR CC, which if integrated into routine practice may improve CT staging accuracy.

ADVANCES IN KNOWLEDGE

Compared to pMMR CC, dMMR CC is at significant risk of N overstaging. Platelet count, CRP and neutrophil count are higher in dMMR CC patients with nodal metastases than those without, and their role in refining clinical staging requires further investigation.