The Diagnostic Performance of MRI for Detection of Extramural Venous Invasion in Colorectal Cancer: A Systematic Review and Meta-Analysis of the Literature.AJR Am J Roentgenol. 2019;213:575-585. [PMID: 31063424 DOI: 10.2214/AJR.19.21112]

Ultra-High-Resolution T2-Weighted PROPELLER MRI of the Rectum With Deep Learning Reconstruction: Assessment of Image Quality and Diagnostic Performance

OBJECTIVE

The aim of this study was to evaluate the impact of ultra-high-resolution acquisition and deep learning reconstruction (DLR) on the image quality and diagnostic performance of T2-weighted periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) imaging of the rectum.

MATERIALS AND METHODS

This prospective study included 34 patients who underwent magnetic resonance imaging (MRI) for initial staging or restaging of rectal tumors. The following 4 types of oblique axial PROPELLER images perpendicular to the tumor were obtained: a standard 3-mm slice thickness with conventional reconstruction (3-CR) and DLR (3-DLR), and 1.2-mm slice thickness with CR (1.2-CR) and DLR (1.2-DLR). Three radiologists independently evaluated the image quality and tumor extent by using a 5-point scoring system. Diagnostic accuracy was evaluated in 22 patients with rectal cancer who underwent surgery after MRI without additional neoadjuvant therapy (median interval between MRI and surgery, 22 days). The signal-to-noise ratio and tissue contrast were measured on the 4 types of PROPELLER imaging.

RESULTS

1.2-DLR imaging showed the best sharpness, overall image quality, and rectal and lesion conspicuity for all readers ( P < 0.01). Of the assigned scores for tumor extent, extramural venous invasion (EMVI) scores showed moderate agreement across the 4 types of PROPELLER sequences in all readers (intraclass correlation coefficient, 0.60-0.71). Compared with 3-CR imaging, the number of cases with MRI-detected extramural tumor spread was significantly higher with 1.2-DLR imaging (19.0 ± 2.9 vs 23.3 ± 0.9, P = 0.03), and the number of cases with MRI-detected EMVI was significantly increased with 1.2-CR, 3-DLR, and 1.2-DLR imaging (8.0 ± 0.0 vs 9.7 ± 0.5, 11.0 ± 2.2, and 12.3 ± 1.7, respectively; P = 0.02). For the diagnosis of histopathologic extramural tumor spread, 3-CR and 1.2-CR had significantly higher specificity than 3-DLR and 1.2-DLR imaging (0.75 and 0.78 vs 0.64 and 0.58, respectively; P = 0.02), and only 1.2-CR had significantly higher accuracy than 3-CR imaging (0.83 vs 0.79, P = 0.01). The accuracy of MRI-detected EMVI with reference to pathological EMVI was significantly lower for 3-CR and 3-DLR compared with 1.2-CR (0.77 and 0.74 vs 0.85, respectively; P < 0.01), and was not significantly different between 1.2-CR and 1.2-DLR (0.85 vs 0.80). Using any pathological venous invasion as the reference standard, the accuracy of MRI-detected EMVI was significantly the highest with 1.2-DLR, followed by 1.2-CR, 3-CR, and 3-DLR (0.71 vs 0.67 vs 0.59 vs 0.56, respectively; P < 0.01). The signal-to-noise ratio was significantly highest with 3-DLR imaging ( P < 0.05). There were no significant differences in tumor-to-muscle contrast between the 4 types of PROPELLER imaging.

CONCLUSIONS

Ultra-high-resolution PROPELLER T2-weighted imaging of the rectum combined with DLR improved image quality, increased the number of cases with MRI-detected extramural tumor spread and EMVI, but did not improve diagnostic accuracy with respect to pathology in rectal cancer, possibly because of false-positive MRI findings or false-negative pathologic findings.

MRI-based radiomic models for the preoperative prediction of extramural venous invasion in rectal cancer: A systematic review and meta-analysis

AIM

To estimate the diagnostic value of magnetic resonance imaging (MRI)-based radiomic models in detecting the extramural venous invasion (EMVI) of rectal cancer.

MATERIALS AND METHODS

Appropriate studies in multiple electronic databases were systematically retrieved. The Quality Assessment of Diagnostic Accuracy Studies 2 and Radiomics Quality Score (RQS) were used to evaluate the eligible studies' methodology quality. Summary accuracy metrics were calculated, and the publication bias was detected using Deek's funnel plot. The sensitivity and meta-regression analysis were performed to investigate the causes of heterogeneity.

RESULTS

For the seven eligible studies, which included 1175 patients, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.80 (95 % CI, 0.70-0.88), 0.89 (95 % CI, 0.84-0.92), 7.0 (95 % CI, 4.7, 10.4), 0.22 (95 % CI, 0.14, 0.34), and 32 (95 % CI, 16, 65), respectively. The area under the receiver operating characteristic curve (AUC) was 0.91 (95 % CI, 0.88, 0.93). Moderate heterogeneity was found due to I2 values of 38.63 % and 32.29 % in sensitivity and specificity, respectively. Meta-regression analysis suggested that the patient enrollment, number of patients, segmentation method, and RQS score were the source of the heterogeneity. The head-to-head analysis suggested that radiomics model had a higher sensitivity for detection of EMVI than subjective evaluation by radiologist (0.47 vs. 0.73, p ≤ 0.001).

CONCLUSION

Our study suggests that MRI-based radiomic models have good diagnostic value in detecting EMVI for rectal cancer patients. Nevertheless, more prospective and high-quality studies with larger sample sizes are needed in the future to validate these results.

Novel biomarkers based on dual-energy computed tomography for risk stratification of very early distant metastasis in colorectal cancer after surgery

Background

Very early distant metastasis (VEDM) for patients with colorectal cancer (CRC) following surgery suggests failure of local treatment strategy and few biomarkers are available for its effective risk stratification. This study aimed to explore the potential of quantitative dual-energy computed tomography (DECT) spectral parameters and build models to predict VEDM.

Methods

Consecutive patients suspected of having CRC and with a clinical indication for enhanced CT from April 2021 to July 2022 at a single institution were prospectively enrolled to undertake spectral CT scanning. The spectral features were extracted by two reviewers and intraclass correlation coefficient (ICC) was used for interobserver agreement evaluation. A total of 16 spectral parameters, including unenhanced effective atomic number, triphasic iodine concentrations (ICs)/normalized ICs (NICs)-A/V/E/1/NIC-A/V/E/spectral curve slopes (λ-A/V/E), two arterial enhancement fractions (AEFs), and venous enhancement fraction (VEF), were determined for analysis. Patients with and without VEDM after surgery were matched using propensity score matching (PSM). The diagnostic performance was assessed using the area under the curve (AUC). Models of multiple modalities were generated.

Results

In total, 222 patients were included (141 males, age range, 32-83 years) and 13 patients developed VEDM. Interobserver agreement ranged from good to excellent (ICC, 0.773-0.964). A total of three spectral parameters (VEF, λ-V, and 1/NIC-V) exhibited significant discriminatory ability (P<0.05) in predicting VEDM, with AUCs of 0.822 [95% confidence interval (CI): 0.667-0.926], 0.738 (95% CI: 0.573-0.866), and 0.713 (95% CI: 0.546-0.846) and optimal cutoff points of 67.16%, 2.46, and 2.44, respectively. The performance of these spectral parameters was validated in the entire cohort; the combined spectral model showed comparable efficiency to the combined clinical model [AUC, 0.771 (95% CI: 0.622-0.919) vs. 0.779 (95% CI: 0.663-0.894), P>0.05]; the clinical-spectral model achieved further improved AUC of 0.887 (95% CI: 0.812-0.962), which was significantly higher than the combined clinical model (P=0.015), yet not superior to the combined spectral model (P=0.078).

Conclusions

Novel spectral parameters showed potential in predicting VEDM in CRC following surgery in this preliminary study, which were closely related with spectral perfusion in the venous phase. However, further studies with larger samples are warranted.

MRI-based radiomics model for preoperative prediction of extramural venous invasion of rectal adenocarcinoma

BACKGROUND

Extramural venous invasion (EMVI) is an important prognostic factor of rectal adenocarcinoma. However, accurate preoperative assessment of EMVI remains difficult.

PURPOSE

To assess EMVI preoperatively through radiomics technology, and use different algorithms combined with clinical factors to establish a variety of models in order to make the most accurate judgments before surgery.

MATERIAL AND METHODS

A total of 212 patients with rectal adenocarcinoma between September 2012 and July 2019 were included and distributed to training and validation datasets. Radiomics features were extracted from pretreatment T2-weighted images. Different prediction models (clinical model, logistic regression [LR], random forest [RF], support vector machine [SVM], clinical-LR model, clinical-RF model, and clinical-SVM model) were constructed on the basis of radiomics features and clinical factors, respectively. The area under the curve (AUC) and accuracy were used to assess the predictive efficacy of different models. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were also calculated.

RESULTS

The clinical-LR model exhibited the best diagnostic efficiency with an AUC of 0.962 (95% confidence interval [CI] = 0.936-0.988) and 0.865 (95% CI = 0.770-0.959), accuracy of 0.899 and 0.828, sensitivity of 0.867 and 0.818, specificity of 0.913 and 0.833, PPV of 0.813 and 0.720, and NPV of 0.940 and 0.897 for the training and validation datasets, respectively.

CONCLUSION

The radiomics-based prediction model is a valuable tool in EMVI detection and can assist decision-making in clinical practice.

Diagnostic accuracy of state-of-the-art rectal MRI sequences for the diagnosis of extramural vascular invasion in locally advanced rectal cancer after preoperative chemoradiotherapy: dos or maybes?

OBJECTIVES

The aim of this study was to determine the accuracy of three state-of-the-art MRI sequences for the detection of extramural venous invasion (EMVI) in locally advanced rectal cancer (LARC) patients after preoperative chemoradiotherapy (pCRT).

METHODS

This retrospective study included 103 patients (median age 66 years old [43-84]) surgically treated with pCRT for LARC and submitted to preoperative contrast-enhanced pelvic MRI after pCRT. T2-weighted, DWI, and contrast-enhanced sequences were evaluated by two radiologists with expertise in abdominal imaging, blinded to clinical and histopathological data. Patients were scored according to the probability of EMVI presence on each sequence using a grading score ranging from 0 (no evidence of EMVI) to 4 (strong evidence of EMVI). Results from 0 to 2 were ranked as EMVI negative and from 3 to 4 as EMVI positive. ROC curves were drawn for each technique, using histopathological results as reference standard.

RESULTS

T2-weighted, DWI, and contrast-enhanced sequences demonstrated an area under the ROC curve (AUC) respectively of 0.610 (95% CI: 0.509-0.704), 0.729 (95% CI: 0.633-0.812), and 0.624 (95% CI: 0.523-0.718). The AUC of DWI sequence was significantly higher than that of T2-weighted (p = 0.0494) and contrast-enhanced (p = 0.0315) sequences.

CONCLUSIONS

DWI is more accurate than T2-weighted and contrast-enhanced sequences for the identification of EMVI following pCRT in LARC patients.

CLINICAL RELEVANCE STATEMENT

MRI protocol for restaging locally advanced rectal cancer after preoperative chemoradiotherapy should routinely include DWI due to its higher accuracy for the diagnosis of extramural venous invasion compared to high-resolution T2-weighted and contrast-enhanced T1-weighted sequences.

KEY POINTS

• MRI has a moderately high accuracy for the diagnosis of extramural venous invasion in locally advanced rectal cancer after preoperative chemoradiotherapy. • DWI is more accurate than T2-weighted and contrast-enhanced T1-weighted sequences in the detection of extramural venous invasion after preoperative chemoradiotherapy of locally advanced rectal cancer. • DWI should be routinely included in the MRI protocol for restaging locally advanced rectal cancer after preoperative chemoradiotherapy.

Predictive value of lesion morphology in rectal cancer based on MRI before surgery

OBJECTIVE

To explore the relationship of MRI morphology of primary rectal cancer with extramural vascular invasion (EMVI), metastasis and local recurrence.

MATERIALS AND METHODS

This retrospective study included 153 patients with rectal cancer. Imaging factors and histopathological index including nodular projection (NP), cord sign (CS) at primary tumor margin, irregular nodules (IN) of mesorectum, MRI-detected peritoneal reflection invasion (PRI), range of rectal wall invasion (RRWI), patterns and length of tumor growth, maximal extramural depth (EMD), histologically confirmed local node involvement (hLN), MRI T stage, MRI N stage, MRI-detected extramural vascular invasion (mEMVI) and histologically confirmed extramural vascular invasion (hEMVI) were evaluated. Determining the relationship between imaging factors and hEMVI, synchronous metastasis and local recurrence by univariate analysis and multivariable logistic regression, and a nomogram validated internally via Bootstrap self-sampling was constructed based on the latter.

RESULTS

Thirty-eight cases of hEMVI, fourteen cases of synchronous metastasis and ten cases of local recurrence were observed among 52 NP cases. There were 50 cases of mEMVI with moderate consistency with hEMVI (Kappa = 0.614). NP, CS, EMD and mEMVI showed statistically significant differences in the negative and positive groups of hEMVI, synchronous metastasis, and local recurrence. Compared to patients with local mass growth, the rectal tumor with circular infiltration had been found to be at higher risk of synchronous metastasis and local recurrence (P < 0.05). NP and IN remained as significant predictors for hEMVI, and mEMVI was a predictor for synchronous metastasis, while PRI and mEMVI were predictors for local recurrences. The nomogram for predicting hEMVI demonstrated a C-index of 0.868, sensitivity of 86.0%, specificity of 79.6%, and accuracy of 81.7%.

CONCLUSION

NP, CS, IN, large EMD, mEMVI, and circular infiltration are significantly associated with several adverse prognostic indicators. The nomogram based on NP has good predictive performance for preoperative EMVI. mEMVI is a risk factor for synchronous metastasis. PRI and mEMVI are risk factors for local recurrence.

Extramural Venous Invasion and Tumor Deposit at Diffusion-weighted MRI in Patients after Neoadjuvant Treatment for Rectal Cancer

Background Diffusion-weighted (DW) imaging is useful in detecting tumor in the primary tumor bed in locally advanced rectal cancer (LARC) after neoadjuvant therapy, but its value in detecting extramural venous invasion (EMVI) and tumor deposit is not well validated. Purpose To evaluate diagnostic accuracy and association with patient prognosis of viable EMVI and tumor deposit on DW images in patients with LARC after neoadjuvant therapy using whole-mount pathology specimens. Materials and Methods This retrospective study included patients who underwent neoadjuvant therapy and surgery from 2018 to 2021. Innovative five-point Likert scale was used by two radiologists to independently evaluate the likelihood of viable EMVI and tumor deposit on restaging DW MRI scans in four axial quadrants (12 to 3 o'clock, 3 to 6 o'clock, 6 to 9 o'clock, and 9 to 12 o'clock). Diagnostic accuracy was assessed at both the per-quadrant and per-patient level, with whole-mount pathology as the reference standard. Weighted κ values for interreader agreement and Cox regression models for disease-free survival and overall survival analyses were used. Results A total of 117 patients (mean age, 56 years ± 12 [SD]; 70 male, 47 female) were included. Pathologically proven viable EMVI and tumor deposit was detected in 29 of 117 patients (25%) and in 44 of 468 quadrants (9.4%). Per-quadrant analyses showed an area under the receiver operating characteristics curve of 0.75 (95% CI: 0.68, 0.83), with sensitivity and specificity of 55% and 96%, respectively. Good interreader agreement was observed between the radiologists (κ = 0.62). Per-patient analysis showed sensitivity and specificity of 62% and 93%, respectively. The presence of EMVI and tumor deposit on restaging DW MRI scans was associated with worse disease-free survival (hazard ratio [HR], 5.6; 95% CI: 2.4, 13.3) and overall survival (HR, 8.9; 95% CI: 1.6, 48.5). Conclusion DW imaging using the five-point Likert scale showed high specificity and moderate sensitivity in the detection of viable extramural venous invasion and tumor deposits in LARC after neoadjuvant therapy, and its presence on restaging DW MRI scans is associated with worse prognosis. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Méndez and Ayuso in this issue.

MRI Assessment of Extramural Venous Invasion Before and After Total Neoadjuvant Therapy for Locally Advanced Rectal Cancer and Its Association with Disease-Free and Overall Survival

BACKGROUND

Extramural venous invasion (EMVI) on baseline MRI is associated with poor prognosis in patients with locally advanced rectal cancer. This study investigated the association of persistent EMVI after total neoadjuvant therapy (TNT) (chemoradiotherapy and systemic chemotherapy) with survival.

METHODS

Baseline MRI, post-TNT MRI, and surgical pathology data from 175 patients with locally advanced rectal cancer who underwent TNT and total mesorectal excision between 2010 and 2017 were retrospectively analyzed for evidence of EMVI. Two radiologists assessed EMVI status with disagreement adjudicated by a third. Pathologic EMVI status was assessed per departmental standards. Cox regression models evaluated the associations between EMVI and disease-free and overall survival.

RESULTS

EMVI regression on both post-TNT MRI and surgical pathology was associated with disease-free survival (hazard ratio, 0.17; 95% confidence interval (CI), 0.04-0.64) and overall survival (hazard ratio, 0.11; 95% CI, 0.02-0.68). In an exploratory analysis of 35 patients with EMVI on baseline MRI, only six had EMVI on pathology compared with 18 on post-TNT MRI; these findings were not associated (p = 0.2). Longer disease-free survival was seen with regression on both modalities compared with remaining positive. Regression on pathology alone, independent of MRI EMVI status, was associated with similar improvements in survival.

CONCLUSIONS

Baseline EMVI is associated with poor prognosis even after TNT. EMVI regression on surgical pathology is common even with persistent EMVI on post-TNT MRI. EMVI regression on surgical pathology is associated with improved DFS, while the utility of post-TNT MRI EMVI persistence for decision-making and prognosis remains unclear.

Artificial intelligence and radiomics in magnetic resonance imaging of rectal cancer: a review

Rectal cancer (RC) is one of the most common tumours worldwide in both males and females, with significant morbidity and mortality rates, and it accounts for approximately one-third of colorectal cancers (CRCs). Magnetic resonance imaging (MRI) has been demonstrated to be accurate in evaluating the tumour location and stage, mucin content, invasion depth, lymph node (LN) metastasis, extramural vascular invasion (EMVI), and involvement of the mesorectal fascia (MRF). However, these features alone remain insufficient to precisely guide treatment decisions. Therefore, new imaging biomarkers are necessary to define tumour characteristics for staging and restaging patients with RC. During the last decades, RC evaluation via MRI-based radiomics and artificial intelligence (AI) tools has been a research hotspot. The aim of this review was to summarise the achievement of MRI-based radiomics and AI for the evaluation of staging, response to therapy, genotyping, prediction of high-risk factors, and prognosis in the field of RC. Moreover, future challenges and limitations of these tools that need to be solved to favour the transition from academic research to the clinical setting will be discussed.

Histogram analysis of dynamic contrast-enhanced magnetic resonance imaging to predict extramural venous invasion in rectal cancer

BACKGROUND

To explore the potential of histogram analysis (HA) of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in the identification of extramural venous invasion (EMVI) in rectal cancer patients.

METHODS

This retrospective study included preoperative images of 194 rectal cancer patients at our hospital between May 2019 and April 2022. The postoperative histopathological examination served as the reference standard. The mean values of DCE-MRI quantitative perfusion parameters (Ktrans, Kep and Ve) and other HA features calculated from these parameters were compared between the pathological EMVI-positive and EMVI-negative groups. Multivariate logistic regression analysis was performed to establish the prediction model for pathological EMVI-positive status. Diagnostic performance was assessed and compared using the receiver operating characteristic (ROC) curve. The clinical usefulness of the best prediction model was further measured with patients with indeterminate MRI-defined EMVI (mrEMVI) score 2(possibly negative) and score 3 (probably positive).

RESULTS

The mean values of Ktrans and Ve in the EMVI-positive group were significantly higher than those in the EMVI-negative group (P = 0.013 and 0.025, respectively). Significant differences in Ktrans skewness, Ktrans entropy, Ktrans kurtosis, and Ve maximum were observed between the two groups (P = 0.001,0.002, 0.000, and 0.033, respectively). The Ktrans kurtosis and Ktrans entropy were identified as independent predictors for pathological EMVI. The combined prediction model had the highest area under the curve (AUC) at 0.926 for predicting pathological EMVI status and further reached the AUC of 0.867 in subpopulations with indeterminate mrEMVI scores.

CONCLUSIONS

Histogram Analysis of DCE-MRI Ktrans maps may be useful in preoperative identification of EMVI in rectal cancer, particularly in patients with indeterminate mrEMVI scores.

Pathologic Implications of Magnetic Resonance Imaging-detected Extramural Venous Invasion of Rectal Cancer

BACKGROUND

Extramural venous invasion (EMVI) is a poor prognostic factor in rectal cancer. Recent advances in magnetic resonance imaging (MRI) allow for the detection of EMVI before surgery. This study aimed to analyze the correlations between MRI-detected EMVI (MR-EMVI) and pathologic parameters in patients with rectal cancer.

MATERIALS AND METHODS

This study retrospectively analyzed 721 patients who underwent radical resection for locally advanced rectal cancer between 2018 and 2019 at the Asan Medical center. All patients underwent an MRI before surgery. The lesions of patients who received neoadjuvant chemoradiation therapy (CRT) were evaluated by MRI before and after the neoadjuvant CRT.

RESULTS

Of the 721 patients, 118 (16.4%) showed a positive MR-EMVI, which significantly correlated with advanced pathologic T-category and N-category, extranodal extension, poor differentiation, lymphatic invasion, venous invasion, and perineural invasion. In addition, MR-EMVI was an independent factor for predicting the pathologic nodal status (OR 3.476, 95% CI, 2.186-5.527, P < .001). Patients with a positive MR-EMVI had a sensitivity of 28.0% and specificity of 91.9% for predicting regional lymph node metastasis, whereas the MR-N category had a sensitivity of 88.7% and specificity of 30.6%. Patients whose MR-EMVI changed from positive to negative after neoadjuvant CRT had no significant differences in pathologic parameters except for lymphatic invasion with patients who were negative before and after neoadjuvant CRT.

CONCLUSION

MR-EMVI correlated with aggressive pathologic features, which indicated a poor prognosis. MR-EMVI may be a complementary imaging biomarker for predicting nodal status and evaluating tumor response to neoadjuvant CRT.

MRI-Based Artificial Intelligence in Rectal Cancer

Rectal cancer (RC) accounts for approximately one-third of colorectal cancer (CRC), with death rates increasing in patients younger than 50 years old. Magnetic resonance imaging (MRI) is routinely performed for tumor evaluation. However, the semantic features from images alone remain insufficient to guide treatment decisions. Functional MRIs are useful for revealing microstructural and functional abnormalities and nevertheless have low or modest repeatability and reproducibility. Therefore, during the preoperative evaluation and follow-up treatment of patients with RC, novel noninvasive imaging markers are needed to describe tumor characteristics to guide treatment strategies and achieve individualized diagnosis and treatment. In recent years, the development of artificial intelligence (AI) has created new tools for RC evaluation based on MRI. In this review, we summarize the research progress of AI in the evaluation of staging, prediction of high-risk factors, genotyping, response to therapy, recurrence, metastasis, prognosis, and segmentation with RC. We further discuss the challenges of clinical application, including improvement in imaging, model performance, and the biological meaning of features, which may also be major development directions in the future. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Quantitative assessment of the microstructure of the mesorectum with different prognostic statuses by intravoxel incoherent motion diffusion-weighed magnetic resonance imaging

BACKGROUND

The mesorectum surrounding the rectum provides an ideal substrate for tumour spread. However, preoperative risk assessment is still an issue. This study aimed to investigate the microstructural features of mesorectum with different prognostic statuses by intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI).

METHODS

Patients with pathologically proven rectal adenocarcinoma underwent routine high-resolution rectal magnetic resonance imaging (MRI) and IVIM DWI sequences were acquired. The MRI-detected circumferential resection margin (mrCRM) and extramural vascular invasion (mrEMVI) were evaluated. IVIM parameters of the mesorectum adjacent to (MAT) and distant from (MDT) the tumour were measured and compared between and within the prognostic factor groups.

RESULTS

The positive mrCRM (p_MAT < 0.001; p_MDT = 0.013) and mrEMVI (p_MAT = 0.001; p_MDT < 0.001) groups demonstrated higher D values in the MAT and MDT than the corresponding negative groups. Conversely, the positive mrCRM (p = 0.001) and mrEMVI (p < 0.001) groups both demonstrated lower f values in the MAT. Similarly, in the self-comparison between the MAT and MDT in the above subgroups, D showed a significant difference in all subgroups (p < 0.001 for all), and f showed a significant difference in the positive mrCRM (p = 0.001) and mrEMVI (p = 0.002) groups. Moreover, the MAT displayed a higher D* in the positive mrCRM (p = 0.014), negative mrCRM (p = 0.009) and negative mrEMVI groups (p < 0.001).

CONCLUSION

The microstructure of the mesorectum in patients with rectal cancer with poor prognostic status shows changes based on IVIM parameters. IVIM parameters might be promising imaging biomarkers for risk assessment of tumour spread in mesorectum preoperatively.

Value of texture analysis based on dynamic contrast-enhanced magnetic resonance imaging in preoperative assessment of extramural venous invasion in rectal cancer

Objective

Accurate preoperative assessment of extramural vascular invasion (EMVI) is critical for the treatment and prognosis of rectal cancer. The aim of our research was to develop an assessment model by texture analysis for preoperative prediction of EMVI.

Materials and methods

This study enrolled 44 rectal patients as train cohort, 7 patients as validation cohort and 18 patients as test cohort. A total of 236 texture features from DCE MR imaging quantitative parameters were extracted for each patient (59 features of Ktrans, Kep, Ve and Vp), and key features were selected by least absolute shrinkage and selection operator regression (LASSO). Finally, clinical independent risk factors, conventional MRI assessment, and T-score were incorporated to construct an assessment model using multivariable logistic regression.

Results

The T-score calculated using the 4 selected key features were significantly correlated with EMVI (p < 0.010). The area under the receiver operating characteristic curve (AUC) was 0.797 for discriminating between EMVI-positive and EMVI-negative patients with a sensitivity of 88.2% and specificity of 70.4%. The conventional MRI assessment of EMVI had a sensitivity of 23.53% and a specificity of 96.30%. The assessment model showed a greatly improved performance with an AUC of 0.954 (sensitivity, 88.2%; specificity, 92.6%) in train cohort, 0.833 (sensitivity, 66.7%; specificity, 100%) in validation cohort and 0.877 in test cohort, respectively.

Conclusions

The assessment model showed an excellent performance in preoperative assessment of EMVI. It demonstrates strong potential for improving the accuracy of EMVI assessment and provide a reliable basis for individualized treatment decisions.

Preoperative prediction of extramural venous invasion in rectal cancer by dynamic contrast-enhanced and diffusion weighted MRI: a preliminary study

Background

To explore the value of the quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters in assessing preoperative extramural venous invasion (EMVI) in rectal cancer.

Methods

Eighty-two rectal adenocarcinoma patients who had underwent MRI preoperatively were enrolled in this study. The differences in quantitative DCE-MRI and DWI parameters including Krans, Kep and ADC values were analyzed between MR-detected EMVI (mrEMVI)-positive and -negative groups. Multivariate logistic regression analysis was performed to build the combined prediction model for pathologic EMVI (pEMVI) with statistically significant quantitative parameters. The performance of the model for predicting pEMVI was evaluated using receiver operating characteristic (ROC) curve.

Results

Of the 82 patients, 24 were mrEMVI-positive and 58 were -negative. In the mrEMVI positive group, the Ktrans and Kep values were significantly higher than those in the mrEMVI negative group (P < 0.01), but the ADC values were significantly lower (P < 0.01). A negative correlation was observed between the Ktrans vs ADC values and Kep vs ADC values in patients with rectal cancer. Among the four quantitative parameters, Ktrans and ADC value were independently associated with mrEMVI by multivariate logistic regression analysis. ROC analysis showed that combined prediction model based on quantitative DCE parameters and ADC values had a good prediction efficiency for pEMVI in rectal cancer.

Conclusion

The quantitative DCE-MRI parameters, Krans, Kep and ADC values play important role in predicting EMVI of rectal cancer, with Ktrans and ADC value being independent predictors of EMVI in rectal cancer.

MRI for Rectal Cancer: Staging, mrCRM, EMVI, Lymph Node Staging and Post-Treatment Response

Rectal cancer is a relatively common malignancy in the United States. Magnetic resonance imaging (MRI) of rectal cancer has evolved tremendously in recent years, and has become a key component of baseline staging and treatment planning. In addition to assessing the primary tumor and locoregional lymph nodes, rectal MRI can be used to help with risk stratification by identifying high-risk features such as extramural vascular invasion and can assess treatment response for patients receiving neoadjuvant therapy. As the practice of rectal MRI continues to expand further into academic centers and private practices, standard MRI protocols, and reporting are critical. In addition, it is imperative that the radiologists reading these cases work closely with surgeons, medical oncologists, radiation oncologists, and pathologists to ensure we are providing the best possible care to patients. This review aims to provide a broad overview of the role of MRI for rectal cancer.

Magnetic Fields and Cancer: Epidemiology, Cellular Biology, and Theranostics

Humans are exposed to a complex mix of man-made electric and magnetic fields (MFs) at many different frequencies, at home and at work. Epidemiological studies indicate that there is a positive relationship between residential/domestic and occupational exposure to extremely low frequency electromagnetic fields and some types of cancer, although some other studies indicate no relationship. In this review, after an introduction on the MF definition and a description of natural/anthropogenic sources, the epidemiology of residential/domestic and occupational exposure to MFs and cancer is reviewed, with reference to leukemia, brain, and breast cancer. The in vivo and in vitro effects of MFs on cancer are reviewed considering both human and animal cells, with particular reference to the involvement of reactive oxygen species (ROS). MF application on cancer diagnostic and therapy (theranostic) are also reviewed by describing the use of different magnetic resonance imaging (MRI) applications for the detection of several cancers. Finally, the use of magnetic nanoparticles is described in terms of treatment of cancer by nanomedical applications for the precise delivery of anticancer drugs, nanosurgery by magnetomechanic methods, and selective killing of cancer cells by magnetic hyperthermia. The supplementary tables provide quantitative data and methodologies in epidemiological and cell biology studies. Although scientists do not generally agree that there is a cause-effect relationship between exposure to MF and cancer, MFs might not be the direct cause of cancer but may contribute to produce ROS and generate oxidative stress, which could trigger or enhance the expression of oncogenes.

The added value of full and reduced field-of-view apparent diffusion coefficient maps for the evaluation of extramural venous invasion in rectal cancer

OBJECTIVE

To investigate the added value of the quantitative analysis of full and reduced field-of-view apparent diffusion coefficient (fADC and rADC) maps for evaluating extramural venous invasion (EMVI) in rectal cancer.

MATERIALS AND METHODS

A total of 94 rectal cancer patients who underwent direct surgical resection were enrolled in this prospective study. The EMVI status of each patient was evaluated on T2-weighted imaging. The mean values of fADC and rADC within the whole tumor were obtained, and histogram parameters were also extracted. Multivariate binary logistic regression analysis was used to analyze independent predictors of EMVI and construct combined models. Receiver operating characteristic (ROC) curves were applied to assess the diagnostic performance.

RESULTS

The energy, skewness, total energy, and kurtosis of fADC map, and the energy and total energy of rADC map were significantly different between the EMVI-positive and EMVI-negative groups (all P < 0.05). Multivariate logistic regression analysis revealed that kurtosis of fADC and circumferential percentage of tumor were independent predictors of EMVI (odds ratio 1.684 and 2.647, P = 0.020 and 0.009). These two parameters combined with subjective evaluation demonstrated the superior diagnostic performance with the area under the ROC curve, sensitivity, specificity, and accuracy of 0.841 (95% CI 0.752-0.909), 0.739, 0.803, and 0.809, respectively.

CONCLUSION

Whole-tumor histogram analysis of ADC map could potentially provide additional information to improve the diagnostic efficiency for assessing EMVI in rectal cancer, which may be beneficial for treatment decision-making.

Unusual Presentation of Treated Colon Cancer with Extramural Venous Invasion: A Case Report

Introduction

Colon cancer is one of the leading malignancies globally and continues to be one of the most typical causes of cancer-related mortality. The clinical outcome of the disease depends on the primary tumour stage, regional nodal involvement and distant disease dissemination. It often presents with haematogenous spread to the liver at the time of diagnosis. Another factor for increased mortality is the presence of extramural venous invasion. This is exceedingly important as it has significant prognostic significance and helps predict survival.

Case Description

A middle-aged female with a recent history of caesarean delivery presented with abdominal pain and occasional constipation, which led to a series of investigations. Initial computed tomography scan showed proximal to mid-transverse colonic tumoural thickening with locoregional lymphadenopathy and solitary distant metastasis in the left hepatic lobe. This was followed by extended right hemicolectomy and hepatic metastasectomy. The patient remained on follow-up and later presented with thrombus formation in the splenoportal circulation. Initially, this was considered a bland thrombus, and the patient was advised a close follow-up. However, the patient was lost to follow and later presented with extensive thrombosis of the portal and splenic veins.

Practical Implications

Confident differentiation of the bland versus malignant thrombosis is crucial to ascertain disease stage and appropriate management. Invasive tissue sampling gives a confident diagnosis of benign versus malignant thrombus. However, using a non-invasive imaging modality, we can still distinguish between the two with reasonable certainty.

Prognostic Significance of EMVI in Rectal Cancer in a Tertiary Cancer Hospital in India

Background  Presence of extramural venous invasion (EMVI) is a poor prognostic factor for rectal cancer as per literature. However, India-specific data are lacking.

Aim  The aim of the study is to determine the prognostic significance of EMVI in locally advanced rectal cancer on baseline MRI.

Materials and Methods  We retrospectively reviewed 117 MRIs of operable non-metastatic locally advanced rectal cancers in a tertiary cancer institute. Three dedicated oncoradiologists determined presence or absence of EMVI, and its length and thickness, in consensus. These patients were treated as per standard institutional protocols and followed up for a median period of 37 months (range: 2–71 months). Kaplan-Meier curves (95% CI) were used to determine disease-free survival (DFS), distant-metastases free survival (DMFS), and overall survival (OS). Univariate analysis was performed by comparing groups with log-rank test.

Results  EMVI positive cases were 34/114 (29%). More EMVI-positive cases developed distant metastasis compared with EMVI-negative cases (14/34–41% vs. 22/83–26%). The difference, however, was not statistically significant ( p  = 0.146). After excluding signet-ring cell cancers ( n  = 14), EMVI showed significant correlation with DMFS ( p  = 0.046), but not with DFS or OS. The median thickness and length of EMVI was 6 and 14 mm, respectively in patients who developed distant metastasis, as compared with 5 and 11 mm in those who did not, although this difference was not statistically significant.

Conclusion  EMVI is a predictor of distant metastasis in locally advanced non-metastatic, non-signet ring cell rectal cancers. EMVI can be considered another high-risk feature to predict distant metastasis.

Radiomics and machine learning applications in rectal cancer: Current update and future perspectives

The high incidence of rectal cancer in both sexes makes it one of the most common tumors, with significant morbidity and mortality rates. To define the best treatment option and optimize patient outcome, several rectal cancer biological variables must be evaluated. Currently, medical imaging plays a crucial role in the characterization of this disease, and it often requires a multimodal approach. Magnetic resonance imaging is the first-choice imaging modality for local staging and restaging and can be used to detect high-risk prognostic factors. Computed tomography is widely adopted for the detection of distant metastases. However, conventional imaging has recognized limitations, and many rectal cancer characteristics remain assessable only after surgery and histopathology evaluation. There is a growing interest in artificial intelligence applications in medicine, and imaging is by no means an exception. The introduction of radiomics, which allows the extraction of quantitative features that reflect tumor heterogeneity, allows the mining of data in medical images and paved the way for the identification of potential new imaging biomarkers. To manage such a huge amount of data, the use of machine learning algorithms has been proposed. Indeed, without prior explicit programming, they can be employed to build prediction models to support clinical decision making. In this review, current applications and future perspectives of artificial intelligence in medical imaging of rectal cancer are presented, with an imaging modality-based approach and a keen eye on unsolved issues. The results are promising, but the road ahead for translation in clinical practice is rather long.

A preliminary study of synthetic magnetic resonance imaging in rectal cancer: imaging quality and preoperative assessment

PURPOSE

To compare the imaging quality, T stage and extramural venous invasion (EMVI) evaluation between the conventional and synthetic T2-weighted imaging (T2WI), and to investigate the role of quantitative values obtained from synthetic magnetic resonance imaging (MRI) for assessing nodal staging in rectal cancer (RC).

METHODS

Ninety-four patients with pathologically proven RC who underwent rectal MRI examinations including synthetic MRI were retrospectively recruited. The image quality of conventional and synthetic T2WI was compared regarding signal-to-noise ratio (SNR), contrast-to-noise (CNR), sharpness of the lesion edge, lesion conspicuity, absence of motion artifacts, and overall image quality. The accuracy of T stage and EMVI evaluation on conventional and synthetic T2WI were compared using the Mc-Nemar test. The quantitative T1, T2, and PD values were used to predict the nodal staging of MRI-evaluated node-negative RC.

RESULTS

There were no statistically significant differences between conventional and synthetic T2WI in SNR, CNR, overall image quality, lesion conspicuity, and absence of motion artifacts (p = 0.058-0.978). There were no significant differences in the diagnostic accuracy of T stage and EMVI between conventional and synthetic T2WI from two observers (p = 0.375 and 0.625 for T stage; p = 0.625 and 0.219 for EMVI). The T2 value showed good diagnostic performance for predicting the nodal staging of RC with the area under the receiver operating characteristic, sensitivity, specificity, and accuracy of 0.854, 90.0%, 71.4%, and 80.3%, respectively.

CONCLUSIONS

Synthetic MRI may facilitate preoperative staging and EMVI evaluation of RC by providing synthetic T2WI and quantitative maps in one acquisition.

MRI-detected extramural venous invasion of rectal cancer: Multimodality performance and implications at baseline imaging and after neoadjuvant therapy

MRI is routinely used for rectal cancer staging to evaluate tumor extent and to inform decision-making regarding surgical planning and the need for neoadjuvant and adjuvant therapy. Extramural venous invasion (EMVI), which is intravenous tumor extension beyond the rectal wall on histopathology, is a predictor for worse prognosis. T2-weighted images (T2WI) demonstrate EMVI as a nodular-, bead-, or worm-shaped structure of intermediate T2 signal with irregular margins that arises from the primary tumor. Correlative diffusion-weighted images demonstrate intermediate to high signal corresponding to EMVI, and contrast enhanced T1-weighted images demonstrate tumor signal intensity in or around vessels. Diffusion-weighted and post contrast images may increase diagnostic performance but decrease inter-observer agreement. CT may also demonstrate obvious EMVI and is potentially useful in patients with a contraindication for MRI. This article aims to review the spectrum of imaging findings of EMVI of rectal cancer on MRI and CT, to summarize the diagnostic accuracy and inter-observer agreement of imaging modalities for its presence, to review other rectal neoplasms that may cause EMVI, and to discuss the clinical significance and role of MRI-detected EMVI in staging and restaging clinical scenarios.

Preoperative evaluation of extramural venous invasion in rectal cancer using radiomics analysis of relaxation maps from synthetic MRI

OBJECTIVE

To establish a radiomics nomogram based on relaxation maps for predicting the extramural venous invasion (EMVI) of rectal cancer (RC) and compare the diagnostic efficacy of the nomogram and subjective assessment by radiologists.

MATERIAL AND METHODS

Among 94 RC patients receiving direct surgical resection, 65 were randomly allocated to the training cohort and 29 to the validation cohort. Radiomics features were extracted from synthetic magnetic resonance imaging including T1, T2, and proton density (PD) maps. The least absolute shrinkage and selection operator methods were used for dimension reduction, feature selection, and radiomics model building. Multivariable logistic regression analysis was used for nomogram development. The performance of the nomogram was assessed with respect to its calibration, receiver operating characteristics (ROC) curve, and decision curve analysis.

RESULTS

The radiomics model demonstrated good predictive efficacy for EMVI, with an area under the ROC curve (AUC), sensitivity, and specificity of 0.912 (95% confidence interval (CI), 0.837-0.986), 0.824, and 0.875 in the training cohort and 0.877 (95% CI 0.751-1.000), 0.833, and 0.826 in the validation cohort. The nomogram had good diagnostic performance, with AUCs of 0.925 (95% CI 0.862-0.988) and 0.899 (95% CI 0.782-1.000) in the training and validation cohort. Furthermore, the radiomics signature showed better diagnostic efficiency than the subjective assessment by both readers (AUC =0.912 vs. 0.732 and 0.763, P = 0.023 and 0.028, respectively).

CONCLUSION

A radiomics nomogram was developed to preoperatively predict EMVI in RC patients. The application of the radiomics model based on relaxation maps could improve the diagnostic efficacy of EMVI.

Prediction of false-negative extramural venous invasion in patients with rectal cancer using multiple mathematical models of diffusion-weighted imaging

PURPOSE

To investigate the parameters from mono-exponential, stretched-exponential, and intravoxel incoherent motion diffusion-weighted imaging (DWI) models for evaluating false-negative extramural venous invasion (EMVI) on conventional magnetic resonance imaging (MRI) in rectal cancer patients.

MATERIAL AND METHODS

Seventy-two rectal cancer patients with negative EMVI on conventional MRI who underwent direct surgical resection were enrolled in this prospective study. The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), and water molecular diffusion heterogeneity index (α) values within the whole tumor were obtained to identify the patients with false-negative EMVI. Receiver operating characteristic (ROC) curves were applied to evaluate the diagnostic performance. Multivariate binary logistic regression analysis was conducted to determine the independent risk factors.

RESULTS

The DDC, D*, f, and α values were significantly different in the EMVI-positive and EMVI-negative groups (P =  0.018, and P <  0.001, respectively). The D*, f, and α values demonstrated good diagnostic performance with area under the ROC curve (AUC) of 0.861, 0.824, and 0.854, respectively. The combined model, including D*, α, and tumor location, proved superior diagnostic performance with the AUC, sensitivity, specificity, and accuracy of 0.971, 0.917, 0.967, and 0.931, respectively. The AUC of the combined model was significantly higher than that of the D*, f, and DDC (P = 0.004, 0.045, and 0.002, respectively).

CONCLUSION

Multi-b-value DWI may be a potential tool for identifying micro-EMVI in rectal cancer. The combination of DWI parameters and tumor location leads to superior diagnostic performance.

Machine Learning-Based Radiomics Nomogram for Detecting Extramural Venous Invasion in Rectal Cancer

Objective

To establish and validate a radiomics nomogram based on the features of the primary tumor for predicting preoperative pathological extramural venous invasion (EMVI) in rectal cancer using machine learning.

Methods

The clinical and imaging data of 281 patients with primary rectal cancer from April 2012 to May 2018 were retrospectively analyzed. All the patients were divided into a training set (n = 198) and a test set (n = 83) respectively. The radiomics features of the primary tumor were extracted from the enhanced computed tomography (CT), the T2-weighted imaging (T2WI) and the gadolinium contrast-enhanced T1-weighted imaging (CE-TIWI) of each patient. One optimal radiomics signature extracted from each modal image was generated by receiver operating characteristic (ROC) curve analysis after dimensionality reduction. Three kinds of models were constructed based on training set, including the clinical model (the optimal radiomics signature combining with the clinical features), the magnetic resonance imaging model (the optimal radiomics signature combining with the mrEMVI status) and the integrated model (the optimal radiomics signature combining with both the clinical features and the mrEMVI status). Finally, the optimal model was selected to create a radiomics nomogram. The performance of the nomogram to evaluate clinical efficacy was verified by ROC curves and decision curve analysis curves.

Results

The radiomics signature constructed based on T2WI showed the best performance, with an AUC value of 0.717, a sensitivity of 0.742 and a specificity of 0.621. The radiomics nomogram had the highest prediction efficiency, of which the AUC was 0.863, the sensitivity was 0.774 and the specificity was 0.801.

Conclusion

The radiomics nomogram had the highest efficiency in predicting EMVI. This may help patients choose the best treatment strategy and may strengthen personalized treatment methods to further optimize the treatment effect.

Preoperative Prediction of Extramural Venous Invasion in Rectal Cancer: Comparison of the Diagnostic Efficacy of Radiomics Models and Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Background: To compare the diagnostic performance of radiomics models with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion parameters for the preoperative prediction of extramural venous invasion (EMVI) in rectal cancer patients and to develop a preoperative nomogram for predicting the EMVI status. Methods: In total, 106 rectal cancer patients were enrolled in our study. All patients under went preoperative rectal high-resolution MRI and DCE-MRI. We built five models based on the perfusion parameters of DCE-MRI (quantitative model), the radiomics of T₂-weighted (T₂W) CUBE imaging (R₁ model), DCE-MRI (R₂ model), clinical features (clinical model), and clinical-radiomics features. The predictive efficacy of the radiomics signature was assessed and internally verified. The area under the receiver operating curve (AUC) was used to compare the diagnostic performance of different radiomics models and DCE-MRI quantitative parameters. The radiomics score and clinical-pathologic risk factors were incorporated into an easy-to-use nomogram. Results: The quantitative parameters K ^trans and Ve were significantly higher in the EMVI-positive group than in the EMVI-negative group (both P =0.02). K ^trans combined with Ve showed a fair degree of accuracy (AUC 0.680 in the training cohort and AUC 0.715 in the validation cohort) compared with K ^trans or Ve alone. The AUCs of the R₁ and R₂ models were 0.826, 0.715 and 0.872, 0.812 in the training and validation cohorts, respectively. In addition, the R₂-C model yielded an AUC of 0.904 in the training cohort and 0.812 in the validation cohort. The nomogram was presented based on the clinical-radiomics model. The calibration curves showed good agreement. Conclusion: The radiomics nomogram that incorporates the radiomics score, histopathological grade and T stage demonstrated better diagnostic accuracy than the DCE-MRI quantitative parameters and may have significant clinical implications for the preoperative individualized prediction of EMVI in rectal cancer patients.

Diagnostic Performance of Vesical Imaging Reporting and Data System for the Prediction of Muscle-invasive Bladder Cancer: A Systematic Review and Meta-analysis

CONTEXT

A noninvasive multiparametric magnetic resonance imaging (MRI)-based scoring system for predicting muscle-invasive bladder cancer (MIBC), the "Vesical Imaging Reporting and Data System" (VI-RADS), was recently developed by an international multidisciplinary panel. Since then, a few studies evaluating the value of VI-RADS for predicting MIBC have been published.

OBJECTIVE

To review the diagnostic performance of VI-RADS for the prediction of MIBC.

EVIDENCE ACQUISITION

PubMed and EMBASE databases were searched up to November 10, 2019. We included diagnostic accuracy studies using VI-RADS to predict MIBC using cystectomy or transurethral resection as the reference standard. Methodological quality was evaluated with Quality Assessment of Diagnostic Accuracy Studies-2. Sensitivity and specificity were pooled and plotted using hierarchical summary receiver operating characteristics (HSROC) modeling. Meta-regression analyses were done to explore heterogeneity.

EVIDENCE SYNTHESIS

Six studies (1770 patients) were included. Pooled sensitivity and specificity were 0.83 (95% confidence interval [CI] 0.70-0.90) and 0.90 (95% CI 0.83-0.95), and the area under the HSROC curve was 0.94 (95% CI 0.91-0.95). Heterogeneity was present among the studies (Q = 29.442, p <  0.01; I² = 87.93%, and 90.99% for sensitivity and specificity). Meta-regression analyses showed that the number of patients (>205 vs ≤205), magnetic field strength (3 vs 1.5 T), T2-weighted image slice thickness (3 vs 4 mm), and VI-RADS cutoff score (≥3 vs ≥4) were significant factors affecting heterogeneity (p ≤  0.03).

CONCLUSIONS

VI-RADS shows good sensitivity and specificity for determining MIBC. Technical factors associated with MRI acquisition and cutoff scores need to be taken into consideration as they may affect performance.

PATIENT SUMMARY

A recently established noninvasive magnetic resonance imaging-based scoring system shows good diagnostic performance in detecting muscle-invasive bladder cancer.

Controversies in Rectal Cancer Treatment and Management

Incorporation of new treatment modalities has significantly increased the complexity of the treatment and management of rectal cancer, including perioperative therapy for local advanced disease and organ preservation for those with response to the preoperative treatment. This review may help practitioners better understand the rationale and selection.

The Impact of Extramural Venous Invasion in Colorectal Cancer: A Detailed Analysis Based on Tumor Location and Evaluation Methods

This study aimed to elucidate the prognostic implications of extramural venous invasion (EMVI) in colorectal cancer (CRC) through a meta-analysis. Eighteen eligible studies were included in this meta-analysis. Data on the prevalence of EMVI and the correlation between EMVI and survival were collected from these studies. In addition, a subgroup analysis was conducted based on tumor location and evaluation methods. The estimated prevalence of EMVI was 28.3% (95% confidence interval [CI] = 23.1% to 34.0%) in patients with CRC. The estimated prevalence of EMVI in patients with colon cancer and rectal cancer was 23.0% (95% CI = 17.6% to 29.6%) and 35.7% (95% CI = 22.3% to 51.6%), respectively. Based on the evaluation method, the estimated prevalence of EMVI were 28.3% (95% CI = 23.2% to 34.1%) and 27.3% (95% CI = 8.4% to 60.6%) in pathologic and radiologic examinations, respectively. The correlation of EMVI with worse overall and disease-free survival rates was significant (hazard ratio = 1.773, 95% CI = 1.483-2.120, and hazard ratio = 2.059, 95% CI = 1.683-2.520, respectively). However, in the subgroup analysis with radiologic examination, there was no significant difference in survival rates between patients with and without EMVI. Our study showed that EMVI was frequently detected in 28.3% of patients with CRC and was correlated to worse survival. The detection of EMVI can be useful for predicting the prognosis of patients with CRC.