CT for lymph node staging of Colon cancer: not only size but also location and number of lymph node count

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.

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.

Applications of new radiological scores: the Node-rads in colon cancer staging

PURPOSE

The study focuses on the evaluation of the new Node Reporting and Data System 1.0 (Node-rads) scoring accuracy in the assessment of metastatic lymph nodes (LN) in patients with colon carcinoma.

MATERIAL AND METHODS

From April 2021 to May 2022, retrospective chart reviews were performed on 67 preoperative CT (Computed Tomography) of patients undergoing excisional surgery for colon cancer at the Polyclinic of Bari, Italy. Primary endpoints were to assess lymph node size and configuration to express the likelihood of a metastatic site adopting the Node-rads score system, whose categories of risk are defined from 1 (very low) to 5 (very high). The nodal postsurgical histological evaluation was the gold standard. The relationship between Node-rads score, LN size, configuration criteria (texture, border and shape) and the presence of histological metastases was statistically evaluated.

RESULTS

All surgical specimens examined had correlation with Node-rads score. They were significantly more likely to present nodes micrometastasis those patients with (a) spherical LN shape (82.8%), (b) with lymph node necrosis (100%), (c) irregular borders (87%) and (d) the LN short axis more than 10 mm (61.9%).

CONCLUSIONS

Our experience highlights how the Node-rads system proposes an intuitive and effective definition of criteria to standardize the lymph node radiological reports in colon cancer disease. Further studies are needed to streamline the classification of the nodal and peripheral LN in all the oncological imaging.

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.

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.

Radiologic T staging of colon cancer: renewed interest for clinical practice

Radiologic imaging, especially MRI, has long been the mainstay for rectal cancer staging and patient selection for neoadjuvant therapy prior to surgical resection. In contrast, colonoscopy and CT have been the standard for colon cancer diagnosis and metastasis staging with T and N staging often performed at the time of surgical resection. With recent clinical trials exploring the expansion of the use of neoadjuvant therapy beyond the anorectum to the remainder of the colon, the current and future state of colon cancer treatment is evolving with a renewed interest in evaluating the role radiology may play in the primary T staging of colon cancer. The performance of CT, CT colonography, MRI, and FDG PET-CT for colon cancer staging will be reviewed. N staging will also be briefly discussed. It is expected that accurate radiologic T staging will significantly impact future clinical decisions regarding the neoadjuvant versus surgical management of colon cancer.

Imaging of colon and rectal cancer

Colon and rectal cancer imaging has traditionally been performed to assess for distant disease (typically lung and liver metastases) and to assess the resectability of the primary tumor. With technological and scientific advances in imaging and the evolution of treatment options, the role of imaging has expanded. Radiologists are now expected to provide a precise description of primary tumor invasion extent, including adjacent organ invasion, involvement of the surgical resection plane, extramural vascular invasion, lymphadenopathy, and response to neoadjuvant treatment, and to monitor for recurrence after clinical complete response.

Size and number of lymph nodes were risk factors of recurrence in stage II colorectal cancer

BACKGROUND

Size and number of lymph nodes (LNs) were reported to be associated with the prognosis of stage II colorectal cancer (CRC). The purpose of this study was to determine the prognostic role of the size of LNs (SLNs) measured by computer tomography (CT) and the number of retrieved LNs (NLNs) in the relapse-free survival (RFS) and overall survival (OS) among stage II CRC patients.

METHODS

Consecutive patients diagnosed with stage II CRC at Fudan University Shanghai Cancer Center (FUSCC) from January 2011 to December 2015 were reviewed, and 351 patients were randomly divided into two cohorts for cross-validation. The optimal cut-off values were obtained using X-tile program. Kaplan-Meier curves and Cox regression analyses were conducted for the two cohorts.

RESULTS

Data from 351 stage II CRC patients were analyzed. The cut-off values for SLNs and NLNs were 5.8 mm and 22, respectively, determined by the X-tile in the training cohort. In the validation cohort, Kaplan-Meier curves demonstrated SLNs (P = 0.0034) and NLNs (P = 0.0451) were positively correlated with RFS but not with OS. The median follow-up time in the training cohort and the validation cohort were 60.8 months and 61.0 months respectively. Univariate and multivariate analysis revealed that both SLNs (training cohort: Hazard Ratio (HR) = 2.361, 95% Confidence interval (CI): 1.044-5.338, P = 0.039; validation cohort: HR = 2.979, 95%CI: 1.435-5.184, P = 0.003) and NLNs (training cohort: HR = 0.335, 95%CI: 0.113-0.994, P = 0.049; validation cohort: HR = 0.375, 95%CI: 0.156-0.900, P = 0.021) were independent prognostic factors for RFS whereas not for OS.

CONCLUSION

SLNs and NLNs are independent prognostic factors for patients with stage II CRC. Patients with SLNs > 5.8 mm and NLNs ≤ 22 are apt to have higher risk of recurrence.

The usefulness of preoperative CT in colon cancer staging: impact of radiologists' experience

PURPOSE

To assess the agreement between radiologists in the detection of specific features related to T- and N-stage and evaluate accuracy in colon cancer staging.

METHODS

Patients who underwent contrast-enhanced computed tomography (CECT) before surgery were enrolled and evaluated by three radiologists with different experience. Pathological data were used as the reference standard. Tumor location, presence of tumor bulging, fat stranding, lateroconal fascia invasion, enlarged vessels, axial short diameter of the biggest node, shape, enhancement pattern, intranodal necrosis, and cluster were collected. Reliability analysis was performed with κ statistics and intraclass correlation coefficients (ICCs). Logistic regressions were used to determine independent predictors associated with staging.

RESULTS

Seventy five patients were evaluated. The reliability analysis was moderate to substantial for tumor location (κ = 0.853), T staging (κ = 0.531), tumor bulging (κ = 0.478), fat stranding (κ = 0.490), lateroconal fascia invasion (κ = 0.436), enlarged vessels (κ = 0.401), the axial short diameter of the biggest node (ICC = 0.732), shape (κ = 0.484), enhancement pattern (κ = 0.431), intranodal necrosis (κ = 0.606), and cluster (κ = 0.358). For all readers, sensitivity was higher for T3 lesions (60-69%) and specificity was higher for T2 and T4 lesions (84.5-90.0% and 82.4-85.1%). The diagnostic accuracy was acceptable for all lesions and among all readers (50.7-92.1%). The lateroconal fascia invasion and enlarged vessels resulted as independent predictor factors (OR = 3.292 and OR = 2.651) for T staging, while nodes' cluster and dimension as independent predictor factors of N staging [OR = 3.798 and OR = 1.083].

CONCLUSION

Reader's experience is one of the most important factors associated with the correct classification of colon cancer. Moreover, CECT can help depict radiological features independently associated with the T and N stages.

A prospective study of diagnostic accuracy of multidisciplinary team and radiology reporting of preoperative colorectal cancer local staging

INTRODUCTION

The aim of this study was to correlate and assess diagnostic accuracy of preoperative staging at multidisciplinary team meeting (MDT) against the original radiology reports and pathological staging in colorectal cancer patients.

METHODS

A prospective observational study was conducted at two institutions. Patients with histologically proven colorectal cancer and available preoperative imaging were included. Preoperative tumor and nodal staging (cT and cN) as determined by the MDT and the radiology report (computed tomography [CT] and/or magnetic resonance imaging [MRI]) were recorded. Kappa statistics were used to assess agreement between MDT and the radiology report for cN staging in colon cancer, cT and cN in rectal cancer, and tumor regression grade (TRG) in patients with rectal cancer who received neoadjuvant therapy. Pathological report after surgery served as the reference standard for local staging, and AUROC curves were constructed to compare diagnostic accuracy of the MDT and radiology report.

RESULTS

A total of 481 patients were included. Agreement between MDT and radiology report for cN stage was good in colon cancer (k = .756, Confidence Interval (CI) 95% .686-.826). Agreement for cT and cN and in rectal cancer was very good (kw = .825, CI 95% .758-.892) and good (kw = .792, CI 95% .709-.875), respectively. In the rectal cancer group that received neoadjuvant therapy, agreement on TRG was very good (kw = .919, CI 95% .846-.993). AUROC curves using pathological staging indicated no difference in diagnostic accuracy between MDT and radiology reports for either colon or rectal cancer.

CONCLUSION

Preoperative colorectal cancer local staging was consistent between specialist MDT review and original radiology reports, with no significant differences in diagnostic accuracy identified.

Multidisciplinary Treatment Strategy for Early Colon Cancer: A Review-An English Version

Treatment for early colon cancer has progressed rapidly, with endoscopic resection and minimally invasive surgery. It is important to select patients without risk of lymph node metastasis before deciding on endoscopic resection for early colon cancer treatment. Pathological risk factors include histologic grade of cancer cell differentiation, lymphovascular invasion, perineural invasion, tumor budding, and deep submucosal invasion. These risk factors for predicting lymph node metastasis are crucial for determining the treatment strategy of endoscopic excision and radical resection for early colon cancer. A multidisciplinary approach is emphasized to establish a treatment strategy for early colon cancer to minimize the risk of complications and obtain excellent oncologic outcomes by selecting an appropriate treatment optimized for the patient's stage and condition. Therefore, we aimed to review the optimal multidisciplinary treatment strategies, including endoscopy and surgery, for early colon cancer.

COL10A1 allows stratification of invasiveness of colon cancer and associates to extracellular matrix and immune cell enrichment in the tumor parenchyma

Background

Treatment options for metastatic colorectal cancer (CRC) are mostly ineffective. We present new evidence that tumor tissue collagen type X alpha 1 (COL10A1) is a relevant candidate biomarker to improve this dilemma.

Methods

Several public databases had been screened to observe COL10A1 expression in transcriptome levels with cell lines and tissues. Protein interactions and alignment to changes in clinical parameters and immune cell invasion were performed, too. We also used algorithms to build a novel COL10A1-related immunomodulator signature. Various wet-lab experiments were conducted to quantify COL10A1 protein and transcript expression levels in disease and control cell models.

Results

COL10A1 mRNA levels in tumor material is clinical and molecular prognostic, featuring upregulation compared to non-cancer tissue, increase with histomorphological malignancy grading of the tumor, elevation in tumors that invade perineural areas, or lymph node invasion. Transcriptomic alignment noted a strong positive correlation of COL10A1 with transcriptomic signature of cancer-associated fibroblasts (CAFs) and populations of the immune compartment, namely, B cells and macrophages. We verified those findings in functional assays showing that COL10A1 are decreased in CRC cells compared to fibroblasts, with strongest signal in the cell supernatant of the cells.

Conclusion

COL10A1 abundance in CRC tissue predicts metastatic and immunogenic properties of the disease. COL10A1 transcription may mediate tumor cell interaction with its stromal microenvironment.

Multidisciplinary treatment strategy for early colon cancer

Background: Treatment for early colon cancer has progressed rapidly with endoscopic resection and minimally invasive surgery. Selection of patients without risk of lymph node metastasis is necessary before deciding on endoscopic resection for early colon cancer treatment. We aimed to review the optimal multidisciplinary treatment strategies for early colon cancer, including endoscopy and surgery.Current Concepts: Pathological risk factors include histologic grade of cancer cell differentiation, lymphovascular invasion, perineural invasion, tumor budding, and deep submucosal invasion. These risk factors for predicting lymph node metastasis are crucial for determining the treatment strategy of endoscopic excision and radical resection for early colon cancer. Prediction of the depth of invasion in early colon cancer using endoscopic optical assessments is vital to determine the appropriate treatment method for endoscopic or surgical resection. Furthermore, optical assessment of pit and vascular patterns is useful for estimating the depth of submucosal invasion using magnifying chromoendoscopy and narrow-band imaging endoscopy. Performing an endoscopic and pathologic evaluation of the risk factors for lymph node metastasis is imperative when selecting endoscopic or surgical resection. Endoscopic treatments include cold snare polypectomy, endoscopic mucosal resection, and endoscopic submucosal dissection. In addition, appropriate surgical treatment should be recommended for patients with early colon cancer with a high risk of lymph node metastasis.Discussion and Conclusion: A multidisciplinary approach should be recommended to establish an optimized treatment strategy, minimize the risk of complications, and obtain excellent oncologic outcomes via patienttailored treatment in patients with early colon cancer.

Anal metastasis of sigmoid colon cancer

A 73‐year‐old man underwent a stage‐Ⅱ sigmoid colon cancer resection. He was carefully monitored, and metastasis or anastomotic recurrence was noted 51 months later. The anal examination revealed a firm pink anal tumor, histologically identified as a metastasis of the colon adenocarcinoma.

Application Value of MRI Combined with MSCT in Diagnosis and Staging of Colon Carcinoma

Objective

To clarify the application value of magnetic resonance imaging (MRI) combined with multislice spiral computed tomography (MSCT) in the diagnosis and staging of colon carcinoma (CC).

Methods

A total of 103 patients with histopathologically diagnosed CC were enrolled. Patient clinical and imaging data were collected, and MRI and MSCT images were analyzed to assess the accuracy of MRI, MSCT, and their combination in diagnosing tumor (T) staging of CC.

Results

Among the 103 cases of histopathologically diagnosed CC, 26 cases (25.24) were in stage T1-2, 72 cases (69.90) were in stage T3, and 5 cases (4.85) were in stage T4. The accuracy of MRI in diagnosing stage T1-2, T3, and T4 was 80.77%, 88.89%, and 60.00%, respectively, with an average of 76.55%. The accuracy rates of MSCT in diagnosing T1-2, T3, and T4 stages were 73.08%, 90.27%, and 60.00%, respectively, with an average of 74.45%. The accuracy rates of MRI+MSCT in diagnosing T1-2, T3, and T4 were 88.46%, 95.83%, and 80.00%, respectively, with an average of 88.10%.

Conclusions

Compared with single use of MRI or MSCT, MRI+MSCT provides accurate imaging data with higher accuracy, which is more helpful for the T-staging evaluation of CC.

CT and 3 Tesla MRI in the TN Staging of Colon Cancer: A Prospective, Blind Study

(1) Background: Computer tomography (CT) scanning is currently the standard method for staging of colon cancer; however, the CT based preoperative local staging is far from optimal. The purpose of this study was to investigate the sensitivity and specificity of magnetic resonance imaging (MRI) compared to CT in the T- and N-staging of colon cancer. (2) Methods: Patients underwent a standard contrast-enhanced CT examination. For the abdominal MRI scan, a 3 Tesla unit was used, including diffusion weighted imaging (DWI). Experienced radiologists reported the CT and MRI scans blinded to each other and the endpoint of the pathological report. (3) Results: From 2018 to 2021, 134 patients received CT and MRI scans. CT identified 118 of the 134 tumors, whereas MRI identified all tumors. For discriminating between stage T3ab and T3cd, the sensitivity of CT was 51.1% and of MRI 80.0% (p = 0.02). CT and MRI showed a sensitivity of 21.4% and 46.4% in detecting pT4 tumors and a specificity of 79.0% and 85.0%, respectively. (4) Conclusion: Compared to CT, the sensitivity of MRI was statistically significantly higher in staging advanced T3cd and T4 tumors. MRI has the potential to be used in the treatment planning of colon cancer.

Accurate staging of non-metastatic colon cancer with CT: the importance of training and practice for experienced radiologists and analysis of incorrectly staged cases

PURPOSE

To investigate whether locoregional staging of colon cancer by experienced radiologists can be improved by training and feedback to minimize the risk of over-staging into the context of patient selection for neoadjuvant therapy and to identify potential pitfalls of CT staging by characterizing pathologic traits of tumors that remain challenging for radiologists.

METHODS

Forty-five cases of stage I-III colon cancer were included in this retrospective study. Five experienced radiologists evaluated the CTs; 5 baseline scans followed by 4 sequential batches of 10 scans. All radiologists were trained after baseline scoring and 2 radiologists received feedback. The learning curve, diagnostic performance, reader confidence, and reading time were evaluated with pathologic staging as reference. Pathology reports and H&E slides of challenging cases were reviewed to identify potential pitfalls.

RESULTS

Diagnostic performance in distinguishing T1-2 vs. T3-4 improved significantly after training and with increasing number of reviewed cases. Inaccurate staging was more frequently related to under-staging rather than over-staging. Risk of over-staging was minimized to 7% in batch 3-4. N-staging remained unreliable with an overall accuracy of 61%. Pathologic review identified two tumor characteristics causing under-staging for T-stage in 5/7 cases: (1) very limited invasive part beyond the muscularis propria and (2) mucinous composition of the invading part.

CONCLUSION

The high accuracy and specificity of T-staging reached in our study indicate that sufficient training and practice of experienced radiologists can ensure high validity for CT staging in colon cancer to safely use neoadjuvant therapy without significant risk of over-treatment, while N-staging remained unreliable.

Imaging features of sentinel lymph node mapped by multidetector-row computed tomography lymphography in predicting axillary lymph node metastasis

INTRODUCTION

Accurately assessing axillary lymph node (ALN) status in breast cancer is vital for clinical decision making and prognosis. The purpose of this study was to evaluate the predictive value of sentinel lymph node (SLN) mapped by multidetector-row computed tomography lymphography (MDCT-LG) for ALN metastasis in breast cancer patients.

METHODS

112 patients with breast cancer who underwent preoperative MDCT-LG examination were included in the study. Long-axis diameter, short-axis diameter, ratio of long-/short-axis and cortical thickness were measured. Logistic regression analysis was performed to evaluate independent predictors associated with ALN metastasis. The prediction of ALN metastasis was determined with related variables of SLN using receiver operating characteristic (ROC) curve analysis.

RESULTS

Among the 112 cases, 35 (30.8%) cases had ALN metastasis. The cortical thickness in metastatic ALN group was significantly thicker than that in non-metastatic ALN group (4.0 ± 1.2 mm vs. 2.4 ± 0.7 mm, P < 0.001). Multi-logistic regression analysis indicated that cortical thickness of > 3.3 mm (OR 24.53, 95% CI 6.58-91.48, P < 0.001) had higher risk for ALN metastasis. The best sensitivity, specificity, negative predictive value(NPV) and AUC of MDCT-LG for ALN metastasis prediction based on the single variable of cortical thickness were 76.2%, 88.5%, 90.2% and 0.872 (95% CI 0.773-0.939, P < 0.001), respectively.

CONCLUSION

ALN status can be predicted using the imaging features of SLN which was mapped on MDCT-LG in breast cancer patients. Besides, it may be helpful to select true negative lymph nodes in patients with early breast cancer, and SLN biopsy can be avoided in clinically and radiographically negative axilla.

Is Laparoscopic Complete Mesocolic Excision and Central Vascular Ligation Really Necessary for All Patients With Right-Sided Colon Cancer?

Colon cancer treatment is on the way to evolution over several decades. The minimally invasive surgery has improved postoperative short-term outcomes. Adjuvant chemotherapy has prolonged the survival of advanced colon cancer patients. Hohenberger proposed the noble concept of complete mesocolic excision (CME) which consists of 3 components: plane surgery, sufficient longitudinal bowel resection, and central vascular ligation (CVL). Mesocolic plane surgery shares the same surgical principle of total mesorectal excision, which is maintaining the intact mesothelial envelope. However, there remain debates about the extent of bowel resection and the level of CVL for maximizing lymph node dissection. There is no solid clinical evidence for the oncological necessity and benefit of extended radical dissection in right hemicolectomy. CME with CVL based on open surgery has been adopted in laparoscopic surgery. So, it is also necessary to look at how the CME could be transformed and successfully implanted in the laparoscopic era. Recent rapid advances in surgical technology and cancer biology are preparing for fundamental changes in cancer surgery. In this study, we reviewed the history, oncological necessity, and compatibility of CME for the right hemicolectomy in the laparoscopic era and outline the new perspectives on the evolution of cancer surgery.