Added value of morphologic characteristics on diffusion-weighted images for characterizing lymph nodes in primary rectal cancer

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

CRITICAL RELEVANCE STATEMENT

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

KEY POINTS

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

Preoperative MR radiomics based on high-resolution T2-weighted images and amide proton transfer-weighted imaging for predicting lymph node metastasis in rectal adenocarcinoma

OBJECTIVES

Lymph node (LN) metastasis is an important prognostic factor in rectal cancer (RC). However, accurate identification of LN metastasis can be challenged for radiologists. The aim of our study was to assess the utility of MRI radiomics based on T2-weighted images (T2WI) and amide proton transfer-weighted (APTw) images for predicting LN metastasis in RC preoperatively.

METHODS

A total of 125 patients with pathologically confirmed rectal adenocarcinoma (RA) from January 2019 to June 2021 who underwent preoperative MR were enrolled in this retrospective study. Radiomics features were extracted from high-resolution T2WI and APTw images of primary tumor. The most relevant radiomics and clinical features were selected using correlation and multivariate logistic analysis. Radiomics models were built using five machine learning algorithms including support vector machine (SVM), logical regression (LR), k- nearest neighbor (KNN), naive bayes (NB), and random forest (RF). The best algorithm was selected for further establish the clinical- radiomics model. The receiver operating characteristic curve (ROC) analysis was used to assess the performance of radiomics and clinical-radiomics model for predicting LN metastasis.

RESULTS

The LR classifier had the best prediction performance, with AUCs of 0.983 (95% CI 0.957-1.000), 0.864 (95% CI 0.729-0.972), 0.851 (95% CI 0.713-0.940) on the training set, validation, and test sets, respectively. In terms of prediction, the clinical-radiomics combined model outperformed the radiomics model. The AUCs of the clinical-radiomics combined model in the validation and test sets were 0.900 (95% CI 0.785-0.986), and 0.929 (95% CI 0.721-0.943), respectively.

CONCLUSION

The radiomics model based on high-resolution T2WI and APTw images can predict LN metastasis accurately in patients with RA.

Diagnostic Performance of Diffusion-Weighted Imaging for Colorectal Cancer Detection: An Updated Systematic Review and Meta-Analysis

Background

Magnetic resonance imaging (MRI), which uses strong magnetic fields and radio waves (radiofrequency energy) to make images, is one of the best imaging methods for soft tissues and can clearly display unique anatomical structures. Diffusion-weighted imaging (DWI) has been developed for identifying various malignant tumors.

Aim

To investigate the diagnostic value of DWI-MRI quantitative analysis in colorectal cancer detection.

Methods

The PubMed, Cochrane Library, and Embase databases were searched from inception to May 29, 2020. Studies published in English that used DWI-MRI for diagnosing colorectal cancer were included. Case reports, letters, reviews, and studies conducted in non-humans or in-vitro experiments were excluded. The pooled diagnostic odds ratio (DOR) and hierarchical summary receiver operating characteristic (HSROC) curves were computed for DWI, and the area under the curve (AUC) and associated standard error (SE) and 95% confidence intervals (CIs) were also used.

Results

In total, 15 studies with 1,655 participants were finally included in this meta-analysis. There were four prospective studies and 11 retrospective studies. Eight studies focused on rectal cancer, six on colorectal cancer, and one on colonic cancer. The performance of DWI-MRI for diagnosing colorectal cancer was accurate, with pooled sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio of 0.88 (95% CI = 0.85–0.91), 0.92 (95% CI = 0.91–0.94), 30.36 (95% CI = 11.05–83.43), and 0.44 (95% CI = 0.30–0.64), respectively. The DOR and HSROC curves were 121 (95% CI = 56–261) and 0.92 (λ: 4.79), respectively.

Conclusion

DWI showed high diagnostic accuracy for colorectal cancer detection. Further studies with large sample sizes and prospective design are needed to confirm these results.

Histogram Analysis of Diffusion-Weighted Magnetic Resonance Imaging as a Biomarker to Predict Lymph Node Metastasis in T3 Stage Rectal Carcinoma

Purpose

This study investigated the predictive value of apparent diffusion coefficient (ADC) histogram parameters of the primary tumor for regional lymph node metastasis (LNM) in pathological T3 stage rectal cancer.

Patients and Methods

We retrospectively studied 175 patients with T3 stage rectal cancer who underwent preoperative MRI, including diffusion-weighted imaging, between January 2015 and October 2017. Based on pathological analysis of surgical specimens, 113 patients were classified into the LN− group and 62 in the LN+ group. We analyzed clinical data, radiological characteristics and histogram parameters derived from ADC maps. Then, receiver operating characteristic curve (ROC) analyses were generated to determine the best diagnostic performance.

Results

The mean (p=0.002, cutoff=1.08×10^–3 s/mm²), coefficient of variation (CV) (p=0.040, cutoff=0.249) of the ADC map, carbohydrate antigen 199, and N stage with magnetic resonance (mrN stage) were independent factors for LNM. Combining these factors yielded the best diagnostic performance, with the area under the ROC curve of 0.838, 72.9% sensitivity, 79.1% specificity, 65.2% positive predictive value, and 84.5% negative predictive value.

Conclusion

With the mean >1.08×10^–3 s/mm² and CV <0.249, the ADC improved the diagnostic performance of LNM in T3 stage rectal cancer, which could assist surgeons with neoadjuvant chemoradiotherapy.

Feasibility and reproducibility of T2 mapping and DWI for identifying malignant lymph nodes in rectal cancer

OBJECTIVES

To evaluate the diagnostic value and reproducibility of T2 mapping versus apparent diffusion coefficients (ADC) for identifying malignant lymph nodes in patients with non-mucinous rectal adenocarcinoma.

METHODS

High-resolution magnetic resonance imaging, diffusion-weighted imaging, and T2 mapping were performed on patients with suspected metastatic lymph nodes in the mesorectum or around the superior rectal artery with a short-axis diameter of 4-10 mm. The T2 and ADC values of pathology-confirmed metastatic versus non-metastatic lymph nodes were compared using the independent-samples t test and receiver operating characteristic curves. Intra- and inter-observer reproducibility were tested. The cutoff value for T2 relaxation time was determined.

RESULTS

In total, 67 lymph nodes underwent histological analysis, with 24 in the non-metastatic and 43 in the metastatic groups. Intra- and inter-observer agreements for T2 values were 0.999 and 0.998, respectively, which were higher than the ADC values of 0.924 and 0.844, respectively. The mean T2 and ADC values for metastatic lymph nodes (65 ± 7.8 ms and 1.17 ± 0.16 × 10^-3 mm²/s, respectively) were significantly lower than for benign lymph nodes(83 ± 5.7 ms and 1.29 ± 0.15 × 10^-3 mm²/s, respectively). T2 values had a higher AUC value of 0.990 than the AUC value for ADC of 0.729. With a cutoff value of 77 ms, sensitivity and specificity for T2 values were 95% and 96%, respectively.

CONCLUSIONS

T2 mapping had higher diagnostic efficacy and reproducibility than ADC and may be useful in differentiating metastatic from non-metastatic lymph nodes in rectal cancer.

KEY POINTS

• Mean T2 values were significantly shorter for malignant versus benign LNs in patients with non-mucinous rectal adenocarcinoma. • The diagnostic efficacy and reproducibility of T2 values were excellent and superior to ADC values.

Diffusion-weighted imaging in rectal cancer: current applications and future perspectives

This review summarizes current applications and clinical utility of diffusion-weighted imaging (DWI) for rectal cancer and in addition provides a brief overview of more recent developments (including intravoxel incoherent motion imaging, diffusion kurtosis imaging, and novel postprocessing tools) that are still in more early stages of research. More than 140 papers have been published in the last decade, during which period the use of DWI have slowly moved from mainly qualitative (visual) image interpretation to increasingly advanced methods of quantitative analysis. So far, the largest body of evidence exists for assessment of tumour response to neoadjuvant treatment. In this setting, particularly the benefit of DWI for visual assessment of residual tumour in post-radiation fibrosis has been established and is now increasingly adopted in clinics. Quantitative DWI analysis (mainly the apparent diffusion coefficient) has potential, both for response prediction as well as for tumour prognostication, but protocols require standardization and results need to be prospectively confirmed on larger scale. The role of DWI for further clinical tumour and nodal staging is less well-defined, although there could be a benefit for DWI to help detect lymph nodes. Novel methods of DWI analysis and post-processing are still being developed and optimized; the clinical potential of these tools remains to be established in the upcoming years.

A Pattern-Based Approach Combining Tumor Morphology on MRI With Distinct Signal Patterns on Diffusion-Weighted Imaging to Assess Response of Rectal Tumors After Chemoradiotherapy

BACKGROUND

Diffusion-weighted imaging is increasingly used in rectal cancer MRI to assess response after chemoradiotherapy. Certain pitfalls (eg, artefacts) may hamper diffusion-MRI assessment, leading to suboptimal diagnostic performance. Combining diffusion-weighted MRI with the underlying morphology on standard (T2-weighted) MRI may help overcome these pitfalls.

OBJECTIVE

The purpose of this study was to evaluate the diagnostic performance of a pattern-based approach combining tumor morphology on T2-weighted MRI with distinct diffusion-weighted imaging signal patterns to assess response after chemoradiotherapy in rectal cancer.

DESIGN

Response to chemoradiotherapy was scored according to 4 patterns: 1) cases with either a clear residual mass with corresponding high-diffusion signal (A+) or completely normalized wall without diffusion signal (A-); 2) cases with circular and/or irregular fibrosis with (B+) or without (B-) small foci of diffusion signal scattered throughout the fibrosis; 3) cases with semicircular fibrosis with (C+) or without (C-) high diffusion signal at the inner margin of the fibrosis; and 4) polypoid tumors showing regression of the polyp and fibrosis at the site of the stalk with (D+) or without (D-) focal high-diffusion signal in the stalk. A total of 75 cases were rescored by an independent second reader to study interobserver variations. Standard of reference was histopathology or long-term outcome.

SETTINGS

The study was conducted at a single tertiary referral center.

PATIENTS

A total of 222 patients with locally advanced rectal cancer undergoing chemoradiotherapy were included.

MAIN OUTCOME MEASURES

Diagnostic performance to discriminate between a complete response and residual tumor was measured.

RESULTS

The pattern-based approach resulted in a sensitivity of 94%, specificity of 77%, positive predictive value of 88%, negative predictive value of 87%, and overall accuracy of 88% to differentiate between tumor versus complete response. Accuracies per pattern were 100% (A), 74% (B), 86% (C), and 92% (D). Interobserver agreement was good (κ = 0.75).

LIMITATIONS

The study included no comparison with routine (nonpattern) diffusion-MRI assessment.

CONCLUSIONS

A pattern-based approach combining tumor morphology with distinct diffusion-weighted imaging patterns results in good diagnostic performance to assess response. See Video Abstract at http://links.lww.com/DCR/A433.

Advanced imaging of colorectal cancer: From anatomy to molecular imaging

Imaging techniques play a key role in the management of patients with colorectal cancer. The introduction of new advanced anatomical, functional, and molecular imaging techniques may improve the assessment of diagnosis, prognosis, planning therapy, and assessment of response to treatment of these patients. Functional and molecular imaging techniques in clinical practice may allow the assessment of tumour-specific characteristics and tumour heterogeneity. This paper will review recent developments in imaging technologies and the evolving roles for these techniques in colorectal cancer.

TEACHING POINTS

• Imaging techniques play a key role in the management of patients with colorectal cancer. • Advanced imaging techniques improve the evaluation of these patients. • Functional and molecular imaging allows assessment of tumour hallmarks and tumour heterogeneity.

Role of quantitative intravoxel incoherent motion parameters in the preoperative diagnosis of nodal metastasis in patients with rectal carcinoma

PURPOSE

To evaluate the diagnostic value of intravoxel incoherent motion imaging (IVIM) in differentiating metastatic and nonmetastatic lymph nodes in patients with rectal carcinoma.

MATERIALS AND METHODS

In all, 68 patients with histologically proven rectal carcinoma underwent an IVIM sequence (b = 0, 25, 50, 75, 100, 150, 200, 400, 600, 800, 1000, 1200, 1500, and 2000 s/mm(2) ) on a 3.0T MRI scanner. The IVIM parameters (D, D*, f, and apparent diffusion coefficient [ADC] values) in metastatic and nonmetastatic lymph nodes were measured and calculated. Receiver-operating characteristic (ROC) analyses were conducted to determine the optimal thresholds, the sensitivities, and specificities for differentiation.

RESULTS

Mean D, f, and ADC values of metastatic lymph nodes were significantly greater than those of the normal lymph nodes (P < 0.01), whereas the mean D* value of metastatic lymph node was statistically lower (P = 0.03). The AUC, sensitivity, specificity, and the cutoff value, respectively, for differentiating metastatic from nonmetastatic lymph nodes for D, D*, f, and ADC were as follows: D, 0.9460, 89.25%, 91.04%, and 1.14 × 10(-3) mm(2) /s; D*, 0.6930, 64.18%, 82.80%, and 7.02 × 10(-3) mm(2) /s; f, 0.7810, 92.47%, 55.22%, and 0.27%; ADC, 0.8970, 87.10%, 88.06%, and 0.80 × 10(-3) mm(2) /s. The ROC curves demonstrated that the area under the ROC (AUC) of the D, ADC, f, and D* values successively decreased, and D had the highest AUC, with D* values being lowest.

CONCLUSION

An IVIM sequence may be helpful in diagnosing metastatic lymph nodes of rectal carcinoma. Average D and ADC values are more sensitive than f and D* values in this differentiation. J. MAGN. RESON. IMAGING 2016;44:1031-1039.