Apparent diffusion coefficient for discriminating metastatic from non-metastatic lymph nodes in primary rectal cancer

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

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

R2* mapping and reduced field-of-view diffusion-weighted imaging for preoperative assessment of nonenlarged lymph node metastasis in rectal cancer

The aim of the current study is to investigate the diagnostic value of R2* mapping versus reduced field-of-view diffusion-weighted imaging (rDWI) of the primary lesion of rectal cancer for preoperative prediction of nonenlarged lymph node metastasis (NLNM). Eighty-one patients with pathologically confirmed rectal cancer underwent preoperative R2* mapping and rDWI sequences before total mesorectal excisions and accompanying regional lymph node dissections. Two radiologists independently performed whole-tumor measurements of R2* and apparent diffusion coefficient (ADC) parameters on primary lesions of rectal cancer. Patients were divided into positive (NLNM+) and negative (NLNM-) groups based on their pathological analysis. The tumor location, maximum diameter of the tumor, and maximum short diameter of the lymph node were assessed. R2* and ADC, pT stage, tumor grade, status of mesorectal fascia, and extramural vascular invasion were also studied for their potential relationships with NLNM using multivariate logistic regression analysis. The NLNM+ group had significantly higher R2* (43.56 ± 8.43 vs. 33.87 ± 9.57, p < 0.001) and lower ADC (1.00 ± 0.13 vs. 1.06 ± 0.22, p = 0.036) than the NLNM- group. R2* and ADC were correlated to lymph node metastasis (r = 0.510, p < 0.001 for R2*; r = -0.235, p = 0.035 for ADC). R2* and ADC showed good and moderate diagnostic abilities in the assessment of NLNM status with corresponding area-under-the-curve values of 0.795 and 0.636. R2* provided a significantly better diagnostic performance compared with ADC for the prediction of NLNM status (z = 1.962, p = 0.0498). The multivariate logistic regression analysis demonstrated that R2* was a compelling factor of lymph node metastasis (odds ratio = 56.485, 95% confidence interval: 5.759-554.013; p = 0.001). R2* mapping had significantly higher diagnostic performance than rDWI from the primary tumor of rectal cancer in the prediction of NLNM status.

Multicenter Evaluation of a Weakly Supervised Deep Learning Model for Lymph Node Diagnosis in Rectal Cancer at MRI

Purpose To develop a Weakly supervISed model DevelOpment fraMework (WISDOM) model to construct a lymph node (LN) diagnosis model for patients with rectal cancer (RC) that uses preoperative MRI data coupled with postoperative patient-level pathologic information. Materials and Methods In this retrospective study, the WISDOM model was built using MRI (T2-weighted and diffusion-weighted imaging) and patient-level pathologic information (the number of postoperatively confirmed metastatic LNs and resected LNs) based on the data of patients with RC between January 2016 and November 2017. The incremental value of the model in assisting radiologists was investigated. The performances in binary and ternary N staging were evaluated using area under the receiver operating characteristic curve (AUC) and the concordance index (C index), respectively. Results A total of 1014 patients (median age, 62 years; IQR, 54-68 years; 590 male) were analyzed, including the training cohort (n = 589) and internal test cohort (n = 146) from center 1 and two external test cohorts (cohort 1: 117; cohort 2: 162) from centers 2 and 3. The WISDOM model yielded an overall AUC of 0.81 and C index of 0.765, significantly outperforming junior radiologists (AUC = 0.69, P < .001; C index = 0.689, P < .001) and performing comparably with senior radiologists (AUC = 0.79, P = .21; C index = 0.788, P = .22). Moreover, the model significantly improved the performance of junior radiologists (AUC = 0.80, P < .001; C index = 0.798, P < .001) and senior radiologists (AUC = 0.88, P < .001; C index = 0.869, P < .001). Conclusion This study demonstrates the potential of WISDOM as a useful LN diagnosis method using routine rectal MRI data. The improved radiologist performance observed with model assistance highlights the potential clinical utility of WISDOM in practice. Keywords: MR Imaging, Abdomen/GI, Rectum, Computer Applications-Detection/Diagnosis Supplemental material is available for this article. Published under a CC BY 4.0 license.

High-resolution integrated dynamic shimming diffusion-weighted imaging (DWI) in the assessment of rectal cancer

OBJECTIVES

To investigate the feasibility of high-resolution integrated dynamic shimming echo planar imaging (iEPI) applied to rectal cancer.

METHODS

A total of seventy-eight patients with non-mucinous rectum adenocarcinoma were enrolled in this study. Using a prototype high-resolution iEPI sequence, high-resolution single-shot EPI (sEPI) sequence, and sEPI sequence, subjective and objective assessment and apparent diffusion coefficient (ADC) value were measured for comparison. The spearman rank correlation analysis test and the receiver operating characteristic curve were performed to evaluate correlation between tumor ADC values, corresponding T stage, and differentiation degree of rectal cancer.

RESULTS

The subjective assessment of the image quality (IQ) of high-resolution iEPI was rated superior to high-resolution sEPI and sEPI by both readers (p < 0.001). Signal-to-noise ratio, contrast-to-noise, and signal-intensity ratio were significantly higher in high-resolution iEPI than the other two sequences (p < 0.001). There was no significant difference of tumor ADC values among three EPI sequences in the group of low- to well-differentiated rectal cancer. An inverse correlation was noted between ADC values on three DWI sequences and pathological T stage of rectal cancer (r =  - 0.693, - 0.689, - 0.640, p < 0.001). The AUC values of high-resolution iEPI, high-resolution sEPI, and sEPI in predicting well-differentiated rectal cancer were 0.910, 0.761, and 0.725 respectively.

CONCLUSIONS

In conclusion, the high-resolution iEPI provided significantly higher IQ and stable ADC compared to another two sequences. High-resolution iEPI has the highest efficacy among three examined sequences in differentiation of rectal cancer with different degrees of differentiation.

KEY POINTS

• High-resolution iEPI provided a significantly better IQ than high-resolution sEPI and sEPI when assessing rectal cancer. • The AUC of high-resolution sEPI was the highest among three EPI sequences in predicting well-differentiated rectal cancer.

Application value of simultaneous multislice readout-segmented echo-planar imaging for diffusion-weighted MRI in differentiation of rectal cancer grade

OBJECTIVE

To analyze the association of apparent diffusion coefficient (ADC) values measured by readout-segmented echo-planar imaging (rs-EPI) using different simultaneous multislice (SMS) acceleration factors and the differentiation of rectal cancer grade.

MATERIALS AND METHODS

Patients with non-mucinous rectal adenocarcinoma diagnosed by biopsy (endoscope-guided biopsy or surgical resection) were retrospectively collected, and each patient underwent an MRI examination. ADC values of rs-EPI, 2 × SMS rs-EPI, and 3 × SMS rs-EPI were recorded as ADC1, ADC2, and ADC3, respectively.

RESULTS

The scanning time of 2 × SMS rs-EPI was 60 s, 56.2% shorter than 137 s of rs-EPI sequence, while that of 3 × SMS rs-EPI was 51 s, 72.8% less than that of rs-EPI time. The ADC value of the three groups dropped with the decrease in cancer grade (p < 0.05). The AUC values of ADC1, ADC2, and ADC3 in predicting highly differentiated rectal cancer were 0.74, 0.729, and 0.687, respectively. The difference in AUC values between ADC1 and ADC2 was not statistically significant (p = 0.889).

DISCUSSION

SMS technology with an acceleration factor of 2 could be applied clinically to evaluate the pathological differentiation of rectal cancer grade.

MRI for nodal restaging after neoadjuvant therapy in rectal cancer with histopathologic comparison

BACKGROUND

After neoadjuvant therapy, most of the lymph nodes (LNs) will shrink and disappear in patients with rectal cancer. However, LNs that are still detectable on MRI carry a risk of metastasis. This study aimed to evaluate the performance of the European Society of Gastrointestinal and Abdominal Radiology (ESGAR) criterion (short-axis diameter ≥ 5 mm) in diagnosing malignant LNs in patients with rectal cancer after neoadjuvant therapy, and whether nodal morphological characteristics (including shape, border, signal homogeneity, and enhancement homogeneity) could improve the diagnostic efficiency for LNs ≥ 5 mm.

METHODS

This retrospective study included 90 patients with locally advanced rectal cancer who underwent surgery after neoadjuvant therapy and performed preoperative MRI. Two radiologists independently measured the short-axis diameter of LNs and evaluated the morphological characteristics of LNs ≥ 5 mm in consensus. With a per node comparison with histopathology as the reference standard, a ROC curve was performed to evaluate the diagnostic performance of the size criterion. For categorical variables, either a χ² test or Fisher's exact test was used.

RESULTS

A total of 298 LNs were evaluated. The AUC for nodal size in determining nodal status was 0.81. With a size cutoff value of 5 mm, the sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 65.9%, 87.0%, 46.8%, 93.6% and 83.9%, respectively. No significant differences were observed in any of the morphological characteristics between benign and malignant LNs ≥ 5 mm (all P > 0.05).

CONCLUSIONS

The ESGAR criterion demonstrated moderate diagnostic performance in identifying malignant LNs in patients with rectal cancer after neoadjuvant therapy. It was effective in determining the status of LNs < 5 mm but not for LNs ≥ 5 mm, and the diagnostic efficiency could not be improved by considering nodal morphological characteristics.

Feasibility of high-resolution readout-segmented echo-planar imaging with simultaneous multislice imaging in assessing rectal cancer

PURPOSE

To investigate the feasibility of high-resolution readout-segmented echo-planar imaging (rs-EPI) with simultaneous multislice (SMS) imaging to predict well-differentiated rectal cancer.Kindly check and confirm whether the Author Name 'Hongyun Huang ' is correctly identified.confirm METHODS: A total of eighty-three patients with nonmucinous rectal adenocarcinoma received both prototype SMS high-spatial-resolution and conventional rs-EPI sequences. Image quality was subjectively assessed by two experienced radiologists using a 4-point Likert scale (1 = poor, 4 = excellent). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and apparent diffusion coefficient (ADC) of the lesion were measured by two experienced radiologists in the objective assessment. Paired t tests or Mann‒Whitney U tests were used to compare the two groups. The areas under the receiver operating characteristic (ROC) curves (AUCs) were used to determine the predictive value of the ADCs in discriminating well-differentiated rectal cancer in the two groups. A two-sided p value < 0.05 represented statistical significance.Please check and confirm if the authors and affiliation details have been correctly identified. Amend if necessary.confirm RESULTS: In the subjective assessment, high-resolution rs-EPI had better image quality than conventional rs-EPI (p < 0.001). High-resolution rs-EPI also had a significantly higher SNR and CNR (p < 0.001). The T stage of rectal cancer was inversely correlated with the ADCs measured on high-resolution rs-EPI (r = -0.622, p < 0.001) and rs-EPI (r = -0.567, p < 0.001). The AUC of high-resolution rs-EPI in predicting well-differentiated rectal cancer was 0.768.

CONCLUSION

High-resolution rs-EPI with SMS imaging provided significantly higher image quality, SNRs, and CNRs and more stable ADC measurements than conventional rs-EPI. Additionally, the pretreatment ADC on high-resolution rs-EPI could discriminate well-differentiated rectal cancer.

Role of apparent diffusion coefficient in assessment of loco-regional nodal spread in cancer rectum: correlative study with histopathological findings

Background

Rectal cancer is associated with high morbidity and mortality rates. Preoperative assessment and detection of nodal metastasis are crucial for selecting a proper treatment plan. Diffusion-weighted imaging is considered to be a crucial functional imaging technique that can aid in determining the condition of lymph nodes. This study aimed to assess the diagnostic utility of MRI functional images by use of apparent diffusion coefficient in regional nodal assessment in rectal cancer.

Results

This study included 54 patients including 29 males (53.7%) and 25 females (46.3%) presented with pathologically proven rectal cancer. Regarding rectal adenocarcinoma, functional MRI imaging using ADC values found to have a better sensitivity (86.24%) in detection of regional nodal metastasis than conventional morphological MRI criteria with 1.05 × 10−3 mm2/s was employed as cutoff value to distinguish metastatic from non-metastatic lymph nodes with statistically significant P value (< 0.001); nevertheless, regarding the accuracy there was no difference (68.52%). As regards mucinous and signet ring cell carcinoma, morphological assessment using conventional MRI sequences were found to have a better accuracy (72.96%) and sensitivity (57.69%) than ADC value, with the latter showed low statistically significant results (P- value < 0.201) in distinguishing metastatic and non-metastatic nodes. This could be explained by extremely high ADC values of nodes for these pathological types owing to their high mucin content.

Conclusions

MRI functional imaging using ADC values can be utilized to distinguish metastatic from non-metastatic lymph nodes in rectal adenocarcinoma employing diagnostic accuracy of 86.52%. However, morphological assessment using conventional MRI was found to be better in assessment of regional lymph nodes at mucinous and signet ring rectal carcinoma.

Development and validation of a high-resolution T2WI-based radiomic signature for the diagnosis of lymph node status within the mesorectum in rectal cancer

Purpose

The aim of this study was to explore the feasibility of a high-resolution T2-weighted imaging (HR-T2WI)-based radiomics prediction model for diagnosing metastatic lymph nodes (LNs) within the mesorectum in rectal cancer.

Method

A total of 604 LNs (306 metastatic and 298 non-metastatic) from 166 patients were obtained. All patients underwent HR-T2WI examination and total mesorectal excision (TME) surgery. Four kinds of segmentation methods were used to select region of interest (ROI), including method 1 along the border of LNs; method 2 along the expanded border of LNs with an additional 2–3 mm; method 3 covering the border of LNs only; and method 4, a circle region only within LNs. A total of 1,409 features were extracted for each method. Variance threshold method, Select K Best, and Lasso algorithm were used to reduce the dimension. All LNs were divided into training and test sets. Fivefold cross-validation was used to build the logistic model, which was evaluated by the receiver operating characteristic (ROC) with four indicators, including area under the curve (AUC), accuracy (ACC), sensitivity (SE), and specificity (SP). Three radiologists with different working experience in diagnosing rectal diseases assessed LN metastasis respectively. The diagnostic efficiencies with each of four segmentation methods and three radiologists were compared to each other.

Results

For the test set, the AUCs of four segmentation methods were 0.820, 0.799, 0.764, and 0.741; the ACCs were 0.725, 0.704, 0.709, and 0.670; the SEs were 0.756, 0.634, 0.700, and 0.589; and the SPs were 0.696, 0.772, 0.717, and 0.750, respectively. There was no statistically significant difference in AUC between the four methods (p > 0.05). Method 1 had the highest values of AUC, ACC, and SE. For three radiologists, the overall diagnostic efficiency was moderate. The corresponding AUCs were 0.604, 0.634, and 0.671; the ACCs were 0.601, 0.632, and 0.667; the SEs were 0.366, 0.552, and 0.392; and the SPs were 0.842, 0.715, and 0.950, respectively.

Conclusions

The proposed HR-T2WI-based radiomic signature exhibited a robust performance on predicting mesorectal LN status and could potentially be used for clinicians in order to determine the status of metastatic LNs in rectal cancer patients.

Establishment of a multi-parameters MRI model for predicting small lymph nodes metastases (<10 mm) in patients with resected pancreatic ductal adenocarcinoma

PURPOSE

To evaluate the potential role of MR findings and DWI parameters in predicting small regional lymph nodes metastases (with short-axis diameter < 10 mm) in pancreatic ductal adenocarcinomas (PDACs).

METHODS

A total of 127 patients, 82 in training group and 45 in testing group, with histopathologically diagnosed PDACs who underwent pancreatectomy were retrospectively analyzed. PDACs were divided into two groups of positive and negative lymph node metastases (LNM) based on the pathological results. Pancreatic cancer characteristics, short axis of largest lymph node, and DWI parameters of PDACs were evaluated.

RESULTS

Univariate and multivariate analyses showed that extrapancreatic distance of tumor invasion, short-axis diameter of the largest lymph node, and mean diffusivity of tumor were independently associated with small LNM in patients with PDACs. The combining MRI diagnostic model yielded AUCs of 0.836 and 0.873, and accuracies of 81.7% and 80% in the training and testing groups. The AUC of the MRI model for predicting LNM was higher than that of subjective MRI diagnosis in the training group (rater 1, P = 0.01; rater 2, 0.008) and in a testing group (rater 1, P = 0.036; rater 2, 0.024). Comparing the subjective diagnosis, the error rate of the MRI model was decreased. The defined LNM-positive group by the MRI model showed significantly inferior overall survival compared to the negative group (P = 0.006).

CONCLUSIONS

The MRI model showed excellent performance for individualized and noninvasive prediction of small regional LNM in PDACs. It may be used to identify PDACs with small LNM and contribute to determining an appropriate treatment strategy for PDACs.

Lymph Nodes Evaluation in Rectal Cancer: Where Do We Stand and Future Perspective

The assessment of nodal involvement in patients with rectal cancer (RC) is fundamental in disease management. Magnetic Resonance Imaging (MRI) is routinely used for local and nodal staging of RC by using morphological criteria. The actual dimensional and morphological criteria for nodal assessment present several limitations in terms of sensitivity and specificity. For these reasons, several different techniques, such as Diffusion Weighted Imaging (DWI), Intravoxel Incoherent Motion (IVIM), Diffusion Kurtosis Imaging (DKI), and Dynamic Contrast Enhancement (DCE) in MRI have been introduced but still not fully validated. Positron Emission Tomography (PET)/CT plays a pivotal role in the assessment of LNs; more recently PET/MRI has been introduced. The advantages and limitations of these imaging modalities will be provided in this narrative review. The second part of the review includes experimental techniques, such as iron-oxide particles (SPIO), and dual-energy CT (DECT). Radiomics analysis is an active field of research, and the evidence about LNs in RC will be discussed. The review also discusses the different recommendations between the European and North American guidelines for the evaluation of LNs in RC, from anatomical considerations to structured reporting.

Diagnostic Efficiency of Diffusion Sequences and a Clinical Nomogram for Detecting Lymph Node Metastases from Rectal Cancer

RATIONALE AND OBJECTIVES

First, to evaluate and compare three different diffusion sequences (i.e., standard DWI, IVIM, and DKI) for nodal staging. Second, to combine the DWI, and anatomic information to assess metastatic lymph node (LN).

MATERIALS AND METHODS

We retrospectively identified 136 patients of rectal adenocarcinoma who met the inclusion criteria. Three diffusion sequences (i.e., standard DWI, IVIM, and DKI) were performed, and quantitative parameters were evaluated. Univariate and multivariate analyses were used to assess the associations between the anatomic and DWI information and LN pathology. Multivariate logistic regression was used to identify independent risk factors. A nomogram model was established, and the model performance was evaluated by the concordance index (c-index) and calibration curve.

RESULTS

There was a statistical difference in variables (LN long diameter, LN short diameter, LN boundary, LN signal, peri-LN signal intensity, ADC_-1000, ADC_-1400, ADC_-2000, K_app and D) between metastatic and non-metastatic LN for training and validation cohorts (p < 0.05). The ADC value derived from b = 1000 mm/s (ADC_-1000) showed the relative higher AUC (AUC = 0.780) than the ADC value derived from b = 1400 mm/s (ADC_-1400) (AUC = 0.703). The predictive accuracy of the nomogram measured by the c-index was 0.854 and 0.812 in the training and validation cohort, respectively.

CONCLUSION

The IVIM and DKI model's diagnostic efficiency was not significantly improved compared to conventional DWI. The diagnostic accuracy of metastatic LN can be enhanced using the nomogram model, leading to a rational therapeutic choice.

An MRI-based multi-objective radiomics model predicts lymph node status in patients with rectal cancer

PURPOSE

To apply a multi-objective radiomics model based on pre-operative magnetic resonance imaging (MRI) for improving diagnostic accuracy of LN metastasis in rectal cancer patients.

METHODS

This study consisted of 91 patients diagnosed with rectal cancer from April 2018 to March 2019. All patients underwent rectal MRI before surgery without any other treatment. Clinical data, subjective radiologist assessments, and radiomic features of LNs were obtained. A total of 1409 radiomic features were extracted from T2WI LN images. Multi-objective optimization with the iterative multi-objective immune algorithm (IMIA) was used to select radiomic features to build prediction models. Predictive performances of radiomic, radiologist, and combined radiomic and radiologist models were assessed for accuracy by receiver operating characteristics (ROC) curves.

RESULTS

For the radiologist analysis, heterogeneity was the only significant independent predictor of LN status. The sensitivity, specificity, and accuracy of the subjective radiologist analysis were 72.09%, 73.81%, and 78.12%, respectively. The sensitivity, specificity, and accuracy of the solitary radiomic model consisting of 10 features were 89.81%, 82.57%, and 87.77%, respectively. The sensitivity, specificity, and accuracy of the combined model, which consisted of 12 radiomic and radiologist features, were 92.23%, 84.69%, and 89.88%, respectively. The combined model had the best prediction performance with an AUC of 0.94.

CONCLUSIONS

The multi-objective radiomics model based on T2WI images was very useful in predicting pre-operative LN status in rectal cancer patients.

Artificial intelligence in rectal cancer

Accurate and rapid diagnosis is essential for correct treatment in rectal cancer. Determining the optimal treatment plan for a patient with rectal cancer is a complex process, and the oncological results and toxicity are not the same in every patient with the same treatment at the same stage. In recent years, the increasing interest in artificial intelligence in all fields of science has also led to the development of innovative tools in oncology. Artificial intelligence studies have increased in many steps from diagnosis to follow-up in rectal cancer. It is thought that artificial intelligence will provide convenience in many ways from personalized treatment to reducing the workload of the physician. Prediction algorithms can be standardized by sharing data between centers, diversifying data, and creating big data.

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.

Apparent diffusion coefficient cannot discriminate metastatic and non-metastatic lymph nodes in rectal cancer: a meta-analysis

BACKGROUND

Our aim was to provide data regarding use of diffusion-weighted imaging (DWI) for distinguishing metastatic and non-metastatic lymph nodes (LN) in rectal cancer.

METHODS

MEDLINE library, EMBASE, and SCOPUS database were screened for associations between DWI and metastatic and non-metastatic LN in rectal cancer up to February 2021. Overall, 9 studies were included into the analysis. Number, mean value, and standard deviation of DWI parameters including apparent diffusion coefficient (ADC) values of metastatic and non-metastatic LN were extracted from the literature. The methodological quality of the studies was investigated according to the QUADAS-2 assessment. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian, and Laird random-effects models with inverse-variance weights were used to account the heterogeneity between the studies. Mean DWI values including 95% confidence intervals were calculated for metastatic and non-metastatic LN.

RESULTS

ADC values were reported for 1376 LN, 623 (45.3%) metastatic LN, and 754 (54.7%) non-metastatic LN. The calculated mean ADC value (× 10^-3 mm²/s) of metastatic LN was 1.05, 95%CI (0.94, 1.15). The calculated mean ADC value of the non-metastatic LN was 1.17, 95%CI (1.01, 1.33). The calculated sensitivity and specificity were 0.81, 95%CI (0.74, 0.89) and 0.67, 95%CI (0.54, 0.79).

CONCLUSION

No reliable ADC threshold can be recommended for distinguishing of metastatic and non-metastatic LN in rectal cancer.

Value of High-resolution MRI in Detecting Lymph Node Calcifications in Patients with Rectal Cancer

RATIONALE AND OBJECTIVES

To analyze CT and high-resolution MRI findings of nodal metastasis calcifications and determine the value of high-resolution MRI in detecting nodal calcifications in rectal cancer patients.

MATERIALS AND METHODS

In total, 229 rectal cancer patients were included. The CT was reviewed for the presence of nodal calcifications by two radiologists. High-resolution two-dimensional turbo spin-echo T2-weighted imaging (2D-TSE-T2WI) and fat-suppressed gadolinium-enhanced isotropic high-resolution three-dimensional gradient-echo T1-weighted imaging (3D-GRE-T1WI) were independently reviewed for nodal calcifications by the two radiologists at one-month and two-month intervals, respectively. The sensitivities, specificities and accuracies of the two high-resolution MRI in detecting nodal calcifications were calculated using CT results as a reference.

RESULTS

Regional calcified metastatic lymph nodes were found in 28 patients. The node-to-node evaluation revealed that 55 (98.2%) of the 56 calcified lymph nodes were metastatic. Fifty-one (92.7%) calcified metastatic lymph nodes displayed scattered fine punctate calcifications to different degrees on CT. In both types of high-resolution MRI, the calcifications demonstrated a patchy area of markedly reduced signal intensity in corresponding areas that were larger than those on CT. The sensitivity and accuracy of fat-suppressed gadolinium-enhanced isotropic high-resolution 3D-GRE-T1WI were significantly higher than those of high-resolution 2D-TSE-T2WI (76.8% vs 58.9%, P = 0.013; 98.3% vs 97.9%, P = 0.007; respectively).

CONCLUSION

Metastatic nodal calcifications are characteristic imaging findings in rectal cancer. Calcifications are indicated by markedly reduced signal on high-resolution MRI, which will alert radiologists to scrutinize CT for nodal calcifications and aid in the accurate diagnosis of metastatic lymph nodes.

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.

A deep learning nomogram kit for predicting metastatic lymph nodes in rectal cancer

Background

Preoperative diagnoses of metastatic lymph nodes (LNs) by the most advanced deep learning technology of Faster Region‐based Convolutional Neural Network (Faster R‐CNN) have not yet been reported.

Materials and Methods

In total, 545 patients with pathologically confirmed rectal cancer between January 2016 and March 2019 were included and were randomly allocated with a split ratio of 2:1 to the training and validation sets, respectively. The MRI images for metastatic LNs were evaluated by Faster R‐CNN. Multivariate regression analyses were used to develop the predictive models. Faster R‐CNN nomograms were constructed based on the multivariate analyses in the training sets and were validated in the validation sets.

Results

The Faster R‐CNN nomogram for predicting metastatic LN status contained predictors of age, metastatic LNs by Faster R‐CNN and differentiation degrees of tumors, with areas under the curves (AUCs) of 0.862 (95% CI: 0.816‐0.909) and 0.920 (95% CI: 0.876‐0.964) in the training and validation sets, respectively. The Faster R‐CNN nomogram for predicting LN metastasis degree contained predictors of metastatic LNs by Faster R‐CNN and differentiation degrees of tumors, with AUCs of 0.859 (95% CI: 0.804‐0.913) and 0.886 (95% CI: 0.822‐0.950) in the training and validation sets, respectively. Calibration plots and decision curve analyses demonstrated good calibrations and clinical utilities. The two nomograms were used jointly as a kit for predicting metastatic LNs.

Conclusion

The Faster R‐CNN nomogram kit exhibits excellent performance in discrimination, calibration, and clinical utility and is convenient and reliable for predicting metastatic LNs preoperatively.

Clinical trial registration: ChiCTR‐DDD‐17013842.

Prediction Model Combining Clinical and MR Data for Diagnosis of Lymph Node Metastasis in Patients With Rectal Cancer

BACKGROUND

Determining the status of lymph node (LN) metastasis in rectal cancer patients preoperatively is crucial for the treatment option. However, the diagnostic accuracy of current imaging methods is low.

PURPOSE

To develop and test a model for predicting metastatic LNs of rectal cancer patients based on clinical data and MR images to improve the diagnosis of metastatic LNs.

STUDY TYPE

Retrospective.

SUBJECTS

In all, 341 patients with histologically confirmed rectal cancer were divided into one training set (120 cases) and three validation sets (69, 103, 49 cases).

FIELD STRENGTH/SEQUENCE

3.0T, axial and sagittal T₂ -weighted turbo spin echo and diffusion-weighted imaging (b = 0 s/mm² , 800 s/mm² ) ASSESSMENT: In the training dataset, univariate logistic regression was used to identify the clinical factors (age, gender, and tumor markers) and MR data that correlated with LN metastasis. Then we developed a prediction model with these factors by multiple logistic regression analysis. The accuracy of the model was verified using three validation sets and compared with the traditional MRI method.

STATISTICAL TESTS

Univariate and multivariate logistic regression. The area under the curve (AUC) value was used to quantify the diagnostic accuracy of the model.

RESULTS

Eight factors (CEA, CA199, ADCmean, mriT stage, mriN stage, CRM, EMVI, and differentiation degree) were significantly associated with LN metastasis in rectal cancer patients (P<0.1). In the training set (120) and the three validation sets (69, 103, 49), the AUC values of the model were much higher than the diagnosis by MR alone (training set, 0.902 vs. 0.580; first validation set, 0.789 vs. 0.743; second validation set, 0.774 vs. 0.573; third validation set, 0.761 vs. 0.524).

DATA CONCLUSION

For the diagnosis of metastatic LNs in rectal cancer patients, our proposed logistic regression model, combining clinical and MR data, demonstrated higher diagnostic efficiency than MRI alone.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY STAGE: 2.

Diffusion-weighted MR volume and apparent diffusion coefficient for discriminating lymph node metastases and good response after chemoradiation therapy in locally advanced rectal cancer

OBJECTIVE

To determine diagnostic performance of diffusion-weighted (DW) magnetic resonance (MR) volume and apparent diffusion coefficient values (ADCs) for assessing lymph node metastases (LNM) and good response after chemoradiation therapy (CRT) in patients with locally advanced rectal cancer (LARC).

MATERIALS AND METHODS

This retrospective study consisted of 61 patients with LARC who underwent pre- and post-CRT DW images. Two radiologists independently placed free-hand regions of interest in each tumor-containing section on DW images to calculate pre- and post-CRT tumor volume and tumor volume reduction rates (Δvolume). Regions of interest were drawn to include tumor on maximum cross-sectional slice to obtain ADCs. Areas under the receiver operating characteristic curves (AUCs) were calculated to evaluate diagnostic performance in identifying LNM and good response after CRT using these parameters.

RESULTS

Inter-observer agreement and intra-observer agreement were excellent for pre- and post-CRT DW MR volume (intraclass correlation coefficient [ICC], 0.889-0.948) and moderate for pre- and post-CRT ADCs (ICC, 0.535-0.811). AUCs for identifying LNM were 0.508 for pre-CRT DW MR volume versus 0.705 for pre-CRT ADC, 0.855 for post-CRT DW MR volume versus 0.679 for post-CRT ADC, and 0.887 for Δvolume versus 0.533 for ΔADC. AUCs for identifying good response were 0.518 for pre-CRT volume versus 0.506 for pre-CRT ADC, 0.975 for post-CRT volume versus 0.723 for post-CRT ADC, and 0.987 for Δvolume versus 0.655 for ΔADC.

CONCLUSION

DW MR Δvolume provided high diagnostic performance in discriminating LNM after CRT. DW MR Δvolume was equally as accurate as post-CRT DW MR volume for evaluating good response.

KEY POINTS

• Inter-observer agreement and intra-observer agreement were excellent for pre- and post-CRT DW MR volume (intraclass correlation coefficient [ICC], 0.889-0.948) and moderate for pre- and post-CRT ADCs (ICC, 0.535-0.811). • DW MR Δvolume provided high diagnostic performance in identifying LNM after CRT (AUC, 0.887) and good response (AUC, 0.987) and was significantly more accurate than pre-CRT DW MR volume (AUC, 0.508 and 0.518, respectively) and ADCs (AUC, 0.705 and 0.506, respectively). • DW MR Δvolume (AUC, 0.987) was equally as accurate as post-CRT DW MR volume (AUC, 0.975) for evaluating good response, while pre-CRT DW MR volume and ADCs were not reliable for evaluating LNM and good response after CRT (AUC, 0.506-0.723).

The role of MRI in the diagnosis and treatment of gastric cancer

Gastric cancer is the fifth most common malignancies and the third leading cause of cancer-related death worldwide, with more than 40% of new cases occurring in China. With the advancement of treatment methods, the application of adjuvant therapy and targeted drugs, the prognosis of patients with gastric cancer has been significantly improved. In recent years, more and more studies have reported that magnetic resonance imaging (MRI) showed great value in the clinical application among patients with gastric cancer, including preoperative staging, treatment response evaluation, predicting prognosis and histopathological features, treatment guidance, and molecular imaging. The remarkable research progress of MRI in gastric cancer will provide new evaluation and treatment approaches for clinical diagnosis and treatment. This article aims to review the current status of the application and research progress of MRI in patients with gastric cancer.

The usefulness of b value threshold map in the evaluation of rectal adenocarcinoma

PURPOSE

To investigate the usefulness of b value threshold (b_Threshold) map in the evaluation of rectal adenocarcinoma by comparing it with diffusion-weighted images and ADC maps regarding lesion detection and the prediction of pathological features.

MATERIALS AND METHODS

Thirty-five patients with rectal tumors were enrolled and underwent axial DWI using a 3-Tesla MRI system. Contrast-to-noise ratio (CNR) between the lesions and normal tissues were assessed on the diffusion-weighted images and b_Threshold maps. Reproducibility for ADC and b_Threshold values were assessed. Significant differences between different groups for pathological prognostic factors were evaluated. Diagnostic performance of ADC and b_Threshold values for those factors were assessed.

RESULTS

Reproducibility was excellent for the ADC and b_Threshold values (ICC 0.985 and 0.992; CV 3.8% and 4.0%) measurements. The CNR between lesions and normal tissues on b_Threshold maps was significantly higher than that on diffusion-weighted images (9.91 ± 5.35 vs. 7.68 ± 3.08, p = 0.012). There were significant differences in the ADC and b_Threshold values between different pathologic differentiation degrees and T stages; significant difference was observed in the b_Threshold values between the different N stage groups (all p values < 0.050). No significant differences were observed between the ROC curves of ADC and the b_Threshold values of rectal lesions for pathologic differentiation and T stage. b_Threshold maps showed good diagnostic performance for N stage.

CONCLUSION

Both ADC and b_Threshold values can differentiate between degrees of pathologic differentiation and T1-2 versus T3-4. Potential added advantages however of the b_Threshold map include a higher CNR compared with DWI images, thereby improving lesion visualization detection, and better diagnostic performance for end staging than ADC. Thus, the b_Threshold map may compliment DWI and ADC to evaluate pathologic features of rectal primary tumors and metastatic lymph nodes.

Higher-order diffusion MRI characterization of mesorectal lymph nodes in rectal cancer

PURPOSE

Mesorectal lymph node staging plays an important role in treatment decision making. Here, we explore the benefit of higher-order diffusion MRI models accounting for non-Gaussian diffusion effects to classify mesorectal lymph nodes both 1) ex vivo at ultrahigh field correlated with histology and 2) in vivo in a clinical scanner upon patient staging.

METHODS

The preclinical investigation included 54 mesorectal lymph nodes, which were scanned at 16.4 T with an extensive diffusion MRI acquisition. Eight diffusion models were compared in terms of goodness of fit, lymph node classification ability, and histology correlation. In the clinical part of this study, 10 rectal cancer patients were scanned with diffusion MRI at 1.5 T, and 72 lymph nodes were analyzed with Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM), Kurtosis, and IVIM-Kurtosis.

RESULTS

Compartment models including restricted and anisotropic diffusion improved the preclinical data fit, as well as the lymph node classification, compared to standard ADC. The comparison with histology revealed only moderate correlations, and the highest values were observed between diffusion anisotropy metrics and cell area fraction. In the clinical study, the diffusivity from IVIM-Kurtosis was the only metric showing significant differences between benign (0.80 ± 0.30 μm² /ms) and malignant (1.02 ± 0.41 μm² /ms, P = .03) nodes. IVIM-Kurtosis also yielded the largest area under the receiver operating characteristic curve (0.73) and significantly improved the node differentiation when added to the standard visual analysis by experts based on T₂ -weighted imaging.

CONCLUSION

Higher-order diffusion MRI models perform better than standard ADC and may be of added value for mesorectal lymph node classification in rectal cancer patients.

MRI-based radiomics of rectal cancer: preoperative assessment of the pathological features

Background

This study aimed to evaluate the significance of MRI-based radiomics model derived from high-resolution T2-weighted images (T2WIs) in predicting tumor pathological features of rectal cancer.

Methods

A total of 152 patients with rectal cancer who underwent surgery without any neoadjuvant therapy between March 2017 and September 2018 were included retrospectively. The patients were scanned using a 3-T magnetic resonance imaging, and high-resolution T2WIs were obtained. Lesions were delineated, and 1029 radiomics features were extracted. Least absolute shrinkage and selection operator was used to select features, and multilayer perceptron (MLP), logistic regression (LR), support vector machine (SVM), decision tree (DT), random forest (RF), and K-nearest neighbor (KNN) were trained using fivefold cross-validation to build a prediction model. The diagnostic performance of the prediction models was assessed using the receiver operating characteristic curves.

Results

A total of 1029 features were extracted, and 15, 11, and 11 features were selected to predict the degree of differentiation, T stage, and N stage, respectively. The best performance of the radiomics model for the degree of differentiation, T stage, and N stage was obtained by SVM [area under the curve (AUC), 0.862; 95% confidence interval (CI), 0.750–0.967; sensitivity, 83.3%; specificity, 85.0%], MLP (AUC, 0.809; 95% CI, 0.690–0.905; sensitivity, 76.2%; specificity, 74.1%), and RF (AUC, 0.746; 95% CI, 0.622-0.872; sensitivity, 79.3%; specificity, 72.2%).

Conclusion

This study demonstrated that the high-resolution T2WI–based radiomics model could serve as pretreatment biomarkers in predicting pathological features of rectal cancer.

Non-invasive MR assessment of the microstructure and microcirculation in regional lymph nodes for rectal cancer: a study of intravoxel incoherent motion imaging

Background

The aim of this study is to evaluate the microstructure and microcirculation of regional lymph nodes (LNs) in rectal cancer by using non-invasive intravoxel incoherent motion MRI (IVIM-MRI), and to distinguish metastatic from non-metastatic LNs by quantitative parameters.

Methods

All recruited patients underwent IVIM-MRI (b = 0, 5, 10, 20, 30, 40, 60, 80, 100, 150, 200, 400, 600, 1000, 1500 and 2000 s/mm²) on a 3.0 T MRI system. One hundred sixty-eight regional LNs with a short-axis diameter equal to or greater than 5 mm from 116 patients were evaluated by two radiologists independently, including 78 malignant LNs and 90 benign LNs. The following parameters were assessed: the short-axis diameter (S), long-axis diameter (L), short- to long-axis diameter ratio (S/L), pure diffusion coefficient (D), pseudo-diffusion coefficient (D^*), and perfusion factor (f). Intraclass correlation coefficients (ICCs) were calculated to assess the interobserver agreement between two readers. Receiver operating characteristic curves were applied for analyzing statistically significant parameters.

Results

Interobserver agreement of IVIM-MRI parameters between two readers was excellent (ICCs> 0.75). The metastatic group exhibited higher S, L and D (P < 0.001), but lower f (P < 0.001) than the non-metastatic group. The area under the curve (95% CI, sensitivity, specificity) of the multi-parameter combined equation for D, f and S was 0.811 (0.744~0.868, 62.82%, 87.78%). The diagnostic performance of the multi-parameter model was better than that of an individual parameter (P < 0.05).

Conclusion

IVIM-MRI parameters provided information about the microstructure and microcirculation of regional LNs in rectal cancer, also improved diagnostic performance in identifying metastatic LNs.

The use of PET/MRI for imaging rectal cancer

Combined PET/MRI is a proposed imaging modality for rectal cancer, leveraging the advantages of MRI and 18F-fluorodeoxyglucose PET. Rectal cancer PET/MRI protocols typically include dedicated pelvis bed positions utilizing small field-of-view T2-weighted imaging. For staging of the primary tumor, PET/MRI can help delineate the extent of tumor better as well as the extent of tumor beyond the muscularis propria. PET uptake may help characterize small lymph nodes, and the use of hepatobiliary phase imaging can improve the detection of small hepatic metastases. The most beneficial aspect of PET/MRI may be in treatment response, although current data are limited on how to combine PET and MRI data in this setting. Limitations of PET/MRI include the inability to detect small pulmonary nodules and issues related to attenuation correction, although the development of new attenuation correction techniques may address this issue. Overall PET/MRI can improve the staging of rectal cancer, although this potential has yet to be fulfilled.

Current concepts in imaging for local staging of advanced rectal cancer

Imaging of rectal cancer has an increasingly pivotal role in the diagnosis, staging, and treatment stratification of patients with the disease. This is particularly true for advanced rectal cancers where magnetic resonance imaging (MRI) findings provide essential information that can change treatment. In this review we describe the rationale for the current imaging standards in advanced rectal cancer for both morphological and functional imaging on the baseline staging and reassessment studies. In addition the clinical implications and future methods by which radiologists may improve these are outlined relative to TNM8.

DWI and T2-Weighted MRI Volumetry in Resectable Rectal Cancer: Correlation With Lymphovascular Invasion and Lymph Node Metastases

OBJECTIVE. The purpose of this study was to assess whether MR volumetric data on DW and T2-weighted MR images are correlated with lymphovascular invasion and lymph node metastases in resectable rectal cancer. MATERIALS AND METHODS. This retrospective study consisted of 50 consecutive patients with rectal cancer who underwent radical surgery within 1 week of MRI. The gross tumor volume was determined on both diffusion-weighted and T2-weighted MR images and correlated with pathologic lymphovascular invasion and lymph node metastases using univariate, multivariate, and ROC curve analyses. RESULTS. Both gross tumor volume values showed correlations with lymphovascular invasion (r = 0.750 vs r = 0.710; p < 0.0001) and lymph node metastases (r = 0.780 vs r = 0.755; p < 0.0001). Both values were associated with lymphovascular invasion and lymph node metastases in univariate analysis (all p < 0.0001), whereas only the DWI-based value was an independent risk factor for lymphovascular invasion (odds ratio = 1.207; p = 0.005) and lymph node metastases (odds ratio = 1.420; p = 0.005) in multivariate analysis. Both values could distinguish between N0 and N1, N0 and N1-N2, and N0-N1 and N2 disease (all p < 0.0001) in the Mann-Whitney U test. The area under the ROC curve was higher for the DWI-based value in lymphovascular invasion (0.899 vs 0.877), N0 vs N1 (0.865 vs 0.827), N0 vs N1-N2 (0.934 vs 0.911), and N0-N1 vs N2 (0.932 vs 0.927). CONCLUSION. Tumor volumetry data correlated with both lymphovascular invasion and lymph node metastases in resectable rectal cancer. In particular, the DWI-based gross tumor volume showed the most potential for noninvasive preoperative evaluation of lymphovascular invasion and lymph node metastases.

Artificial intelligence system of faster region-based convolutional neural network surpassing senior radiologists in evaluation of metastatic lymph nodes of rectal cancer

BACKGROUND

An artificial intelligence system of Faster Region-based Convolutional Neural Network (Faster R-CNN) is newly developed for the diagnosis of metastatic lymph node (LN) in rectal cancer patients. The primary objective of this study was to comprehensively verify its accuracy in clinical use.

METHODS

Four hundred fourteen patients with rectal cancer discharged between January 2013 and March 2015 were collected from 6 clinical centers, and the magnetic resonance imaging data for pelvic metastatic LNs of each patient was identified by Faster R-CNN. Faster R-CNN based diagnoses were compared with radiologist based diagnoses and pathologist based diagnoses for methodological verification, using correlation analyses and consistency check. For clinical verification, the patients were retrospectively followed up by telephone for 36 months, with post-operative recurrence of rectal cancer as a clinical outcome; recurrence-free survivals of the patients were compared among different diagnostic groups, by methods of Kaplan-Meier and Cox hazards regression model.

RESULTS

Significant correlations were observed between any 2 factors among the numbers of metastatic LNs separately diagnosed by radiologists, Faster R-CNN and pathologists, as evidenced by rradiologist-Faster R-CNN of 0.912, rPathologist-radiologist of 0.134, and rPathologist-Faster R-CNN of 0.448 respectively. The value of kappa coefficient in N staging between Faster R-CNN and pathologists was 0.573, and this value between radiologists and pathologists was 0.473. The 3 groups of Faster R-CNN, radiologists and pathologists showed no significant differences in the recurrence-free survival time for stage N0 and N1 patients, but significant differences were found for stage N2 patients.

CONCLUSION

Faster R-CNN surpasses radiologists in the evaluation of pelvic metastatic LNs of rectal cancer, but is not on par with pathologists.

TRIAL REGISTRATION

www.chictr.org.cn (No. ChiCTR-DDD-17013842).

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.

The clinical application value of MR diffusion-weighted imaging in the diagnosis of rectal cancer: A retrospective study

The present study evaluated the clinical potential of magnetic resonance (MR) diffusion-weighted imaging (DWI) in the diagnosis of rectal cancer.A total of 84 patients confirmed with rectal cancer were used as study subjects in the present study. All patients received conventional sequence MR T1WI, T2WI, and DWI examination as well as operative pathological examination. The differences between the MRI results and operative pathological results were analyzed.The diagnosis accordance rates of conventional sequence examination in stage T1, T2, T3, and T4 were 60.00%, 82.75%, 62.85%, and 80.00%, respectively. The diagnosis accordance rates of conventional sequence combined with DWI examination in stages T1, T2, T3, and T4 were 100.00%, 100.00%, 82.85%, and 100.00% respectively. The total diagnosis accordance rates in the T staging of rectal cancer with conventional (Routinely or generally applied) sequence examination and conventional sequence combined with DWI examination were 71.42% and 92.85%, respectively.The analysis on consistency of MR conventional sequence examination suggested that the conventional sequence combined with DWI examination is more consistent with pathological staging when compared with the convention sequence examination alone. MR DWI combined with conventional sequences reveals quite good accuracy in the T staging of rectal cancer.

Role of Quantitative Dynamic Contrast-Enhanced MRI in Evaluating Regional Lymph Nodes With a Short-Axis Diameter of Less Than 5 mm in Rectal Cancer

OBJECTIVE

The aim of this study was to discriminate metastatic from nonmetastatic regional lymph nodes (LNs) with short-axis diameters of less than 5 mm in rectal cancer using quantitative parameters derived from dynamic contrast-enhanced (DCE) MRI.

SUBJECTS AND METHODS

Sixty-five LNs from 122 patients were evaluated, including malignant LNs (n = 27) and benign LNs (n = 38). The following parameters were assessed: the forward volume transfer constant (K^trans), reverse volume transfer constant (k_ep), fractional extravascular extracellular space volume (Ve), short-axis diameter, long-axis diameter, and short- to long-axis diameter ratio. ROC curves were used to analyze statistically significant parameters.

RESULTS

Metastatic LNs exhibited a lower K^trans than did nonmetastatic LNs (p < 0.001), but the other parameters were not significantly different between the two groups. The AUC of the K^trans was 0.732, with a 95% CI of 0.610-0.854, and the diagnostic cutoff value was 0.088 min^-1 (sensitivity, 60.5%; specificity, 81.5%).

CONCLUSION

K^trans had moderate diagnostic performance in assessing small regional LNs in rectal cancer and appears to be a useful predictor when distinguishing malignant LNs from benign LNs only by morphology is difficult.

Z-Score transformation of ADC values: A way to universal cut off between malignant and benign lymph nodes

PURPOSE

To determine the possibility of a universal cut off value between benign and malignant lymph nodes in patients with tumour by Z-Score transformation method.

MATERIALS AND METHODS

Diffusion weighted imaging, ADC measurements of malignant and benign lymph nodes of 6 studies (4 body parts), conducted for 5 times, in two institutions with variable technical details were analyzed in their original value as well as the standardized Z-Score value. The standardized Z-Score value was obtained by subtracting the population mean of the control group from an individual raw score and then dividing the difference by the population standard deviation of the control group. General cut off values were obtained by both Mega-analysis by receiver operator characteristic curve analysis, when data from the 6 studies were combined and Meta-analysis with weighting coefficients and cut off values of the six individual studies. Sensitivity, specificity and accuracy with cut offs from individual studies, meta-analysis and mega-analysis were calculated. Kappa test was performed to assess the consistency of diagnostic test accuracy, between optimized cut offs of individual studies and the proposed universal cut offs obtained from meta-analysis and mega-analysis.

RESULTS

The ADC values of benign and malignant lymph nodes are significantly different, but with large overlap across the studies. The overlap can be minimized by Z-Score transformation. The result of ROC analysis of the collective Z-Score transformed ADC values of 6 studies was superior to that of the collective original ADC values (sensitivity: 87.4% versus 67.2%, specificity: 90.5% versus 87.9%, accuracy: 89.6% versus 81.4%). The universal Z-Score cut off from Meta-analysis is also better than the original ADC cut off (sensitivity: 82.8% versus 76.3%, specificity 92.6% versus 62.9%, accuracy 89.6% versus 67.1%). Applied to the individual studies, the universal transformed Z-Score cut offs produced superior consistency with the individual optimal cut offs (individual and meta Z-Score: 0.7228-0.9793; individual and mega Z-Score: 0.7111-0.9169) compared with the universal original ADC cut offs (individual and meta ADC: 0.3030-1.0000; individual and mega ADC 0.3268-0.9618).

CONCLUSION

Z-Score transformation could minimize inter-study variations due to heterogeneity of MR systems and sequence parameters, and provide a more consistent universal cut off value between benign and malignant nodes across studies.

Are ADC values of readout-segmented echo-planar diffusion-weighted imaging (RESOLVE) correlated with pathological prognostic factors in rectal adenocarcinoma?

Background

Diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC) values as imaging biomarkers of rectal cancer are currently a hot research spot. The use of ADC values for preoperative judgment of pathological features in rectal cancer has been generally accepted. The image quality evaluation of conventional diffusion is severe deformation, and the measurement of ADC values can easily lead to bias. Readout-segmented echo-planar diffusion-weighted imaging (RESOLVE) provides high signal-to-noise ratio images and significantly reduces distortions caused by magnetosensitive effects. The purpose of this study was to explore the correlations between ADC values of RESOLVE and pathological prognostic factors in rectal adenocarcinoma.

Methods

We collected pathological data of 89 patients with pathologically confirmed rectal adenocarcinoma who directly underwent surgical resection without receiving adjuvant therapy. The patients were grouped according to the pathologic type, gross classification, degree of differentiation, TN stage, and immunohistochemical expression of epidermal growth factor receptor (EGFR).

Results

RESOLVE ADC values of rectal cancer were measured at b = 800, and correlations between the RESOLVE ADC values obtained in different groups were analysed. We found that RESOLVE ADC values in the ulcer-type group were significantly higher than those in the eminence-type group.

Conclusion

RESOLVE ADC values in different pathologic types of rectal cancer were significantly different. RESOLVE ADC values in the EGFR-positive group were significantly lower than those in the EGFR-negative group. There was no significant difference in RESOLVE ADC values between different degrees of pathologic differentiation, TN stages, and positive or negative lymph nodes. The quantitative description of RESOLVE ADC values could be used to assess the biological behaviour of rectal adenocarcinoma.

Application of Diffusion Kurtosis Imaging and Histogram Analysis for Assessing Preoperative Stages of Rectal Cancer

Objective

To explore the value of diffusion kurtosis imaging (DKI) and histogram analysis for assessing preoperative stages and heterogeneity in rectal cancer.

Methods

Fifty patients with pathologically confirmed rectal adenocarcinoma were enrolled. The value of DKI parameters and histogram metrics for assessing the preoperative stages and heterogeneity in rectal cancer was analyzed retrospectively.

Results

(1) ADC-10th percentile and ADC-25th percentile were significantly higher in T1-2 than in the T3-4 rectal cancer (the ADC values were 0.65 ± 0.08 × 10⁻³ mm²/s versus 0.58 ± 0.11 × 10⁻³ mm²/s and 0.73 ± 0.11 × 10⁻³ mm²/s versus 0.65 ± 0.11 × 10⁻³ mm²/s; p values were 0.035 and 0.024, resp.). (2) D-10th percentile and D-25th percentile were also significantly higher in T1-2 than in T3-4 rectal cancer (the D values were 0.96 ± 0.19 × 10⁻³ mm²/s versus 0.84 ± 0.16 × 10⁻³ mm²/s and 1.15 ± 0.27 × 10⁻³ mm²/s versus 0.99 ± 0.18 × 10⁻³ mm²/s; p values were 0.017 and 0.044, resp.). (3) K value and its histogram metrics showed no statistically significant difference between T1-2 and T3-4. (4) D-10th had the largest area under the curve (AUC 0.799) among all the parameters; the sensitivity and specificity were 84.2 and 61.3%, respectively. (5) DKI combined with traditional MRI had an accuracy of 68% while assessing the lymph node of rectal cancer.

Conclusion

DKI parameters and histogram metrics are rather valuable in assessing the preoperative stages of rectal cancer; D-10th percentile exhibits the highest diagnostic efficiency.

Prediction of lateral pelvic lymph node metastasis in patients with locally advanced rectal cancer with preoperative chemoradiotherapy: Focus on MR imaging findings

PURPOSE

To investigate the predictive factors for lateral pelvic lymph node (LPLN) metastasis in patients with locally advanced rectal cancer treated with preoperative chemoradiotherapy (CRT).

MATERIALS AND METHODS

Fifty-seven patients with locally advanced rectal cancer and LPLNs larger than 5 mm underwent LPLN dissection (LPLD) after preoperative CRT. The MRI findings, including the apparent diffusion coefficient value and LPLN size reduction rate before/after CRT; clinical factors; and pathologic results were evaluated to identify the predictive factors associated with LPLN metastasis.

RESULTS

LPLN metastasis was confirmed in 23 patients (40.4%). Metastasis was significantly higher in LPLNs with multiplicity, short-axis diameter ≥8 mm before CRT, short-axis diameter >5 mm after CRT, size reduction rate ≤33.3%, heterogeneous signal intensity, and irregular margin (P<0.05) on MR. Multivariable analysis showed that pre-CRT short-axis diameter of LPLNs ≥8 mm, size reduction rate ≤33.3%, and heterogeneous signal intensity were independently associated with LPLN metastasis.

CONCLUSIONS

The size and signal intensity of LPLN before and after CRT are useful MRI findings to predict LPLN metastasis and are helpful to determine the indications for LPLD.

Diffusion kurtosis imaging in identifying the malignancy of lymph nodes during the primary staging of rectal cancer

AIM

The aim was to assess the diagnostic value of diffusion kurtosis imaging (DKI) for discriminating between benign and malignant lymph nodes in patients with rectal carcinoma.

METHOD

ighty-five patients with rectal adenocarcinoma who underwent total mesorectal excision of the rectum were studied. A total of 273 lymph nodes were harvested and subjected to histological analysis. Quantitative parameters [apparent diffusion parameter D_app of the Gaussian distribution, apparent kurtosis coefficient K_app and apparent diffusion coefficient (ADC)] of lymph nodes were derived from DKI. Differences and the diagnostic performance of these parameters were calculated by using the independent-samples t test and receiver operating characteristic curve analyses.

RESULTS

The median D_app and ADC values of metastatic lymph nodes were significantly greater than those of benign lymph nodes, whereas the median K_app of metastatic lymph nodes was statistically less than that of normal lymph nodes. D_app had the relatively highest area under the curve of 0.774. When 1126.15 × 10^-6  mm² /s was used as a D_app threshold value, the sensitivity and specificity were 96.97% and 41.82%, respectively.

CONCLUSION

DKI can help differentiate metastatic vs benign lymph nodes during the primary staging of rectal cancer.

Magnetic resonance imaging of rectal cancer

Magnetic resonance imaging (MRI) is still the most commonly used imaging technique for the diagnosis of rectal cancer with the highest degree of accuracy, and it is also recommended by the National Comprehensive Cancer Network, European Society for Medical Oncology, and Chinese guidelines for diagnosis and treatment of colorectal cancer. The application of diffusion weighted imaging, apparent diffusion coefficient, diffusion weighted imaging with background signal suppression, intravoxel incoherent motion, perfusion imaging, magnetic resonance spectroscopy, and molecular imaging has provided many choices for tumor detection and preoperative staging, differential diagnosis of benign and malignant rectum lesions, postoperative follow-up, recurrence monitoring, and efficacy evaluation. We believe that with the development of basic theory and related technology, MRI for rectal cancer assessment will become more efficient.

Pretreatment magnetic resonance imaging of regional lymph nodes with carcinoembryonic antigen in prediction of synchronous distant metastasis in patients with rectal cancer

Distant metastasis in patients with rectal cancer remains a problem influencing prognosis. Prediction of synchronous distant metastasis is important for the choice of personalized treatment strategies and postoperative follow-up protocol. So far, there are few studies about the predictive value of MRI features combined with clinical characteristics for synchronous distant metastasis in rectal cancer, especially for the lesions developed within 6 months after surgery. We retrospectively reviewed the pretreatment clinical characteristics and magnetic resonance imaging (MRI) features of 271 patients from January 2010 to December 2011with pathologically confirmed rectal adenocarcinoma and tried to identify independent risk factors for synchronous distant metastasis. Forty-nine patients (18.1%) were confirmed to have synchronous distant metastasis. Multivariate logistic regression model demonstrated that the elevated carcinoembryonic antigen (CEA), positive MRI-predicted lymph nodes staging (mrN), and MRI-predicted mesorectal fascia (mrMRF) involvement were independent risk factors. The odd ratios were 12.2 for elevated CEA, 5.4 for mrN1 and 7.6 for mrN2, and 3.8 for mrMRF involvement, respectively. The accuracy and specificity for predicting synchronous distant metastasis by evaluating the positive mrN combined with elevated CEA were improved to 87.8% and 94.6%, respectively. The accuracy, sensitivity and specificity of positive mrN assessment were 86.1%, 71.4% and 91.7%, respectively using the histopathologic results as the reference standard. Altogether, our findings suggest that pretreatment positive mrN and elevated CEA are independent risk factors for synchronous distant metastasis in rectal cancer and combination of both could help to recognize the patients with high risk for structuring personalized treatment protocol.

Comparison of DWI and 18F-FDG PET/CT for assessing preoperative N-staging in gastric cancer: evidence from a meta-analysis

The diagnostic values of diffusion weighted imaging (DWI) and ¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) for N-staging of gastric cancer (GC) were identified and compared. After a systematic search to identify relevant articles, meta-analysis was used to summarize the sensitivities, specificities, and areas under curves (AUCs) for DWI and PET/CT. To better understand the diagnostic utility of DWI and PET/CT for N-staging, the performance of multi-detector computed tomography (MDCT) was used as a reference. Fifteen studies were analyzed. The pooled sensitivity, specificity, and AUC with 95% confidence intervals of DWI were 0.79 (0.73–0.85), 0.69 (0.61–0.77), and 0.81 (0.77–0.84), respectively. For PET/CT, the corresponding values were 0.52 (0.39–0.64), 0.88 (0.61–0.97), and 0.66 (0.62–0.70), respectively. Comparison of the two techniques revealed DWI had higher sensitivity and AUC, but no difference in specificity. DWI exhibited higher sensitivity but lower specificity than MDCT, and ¹⁸F-FDG PET/CT had lower sensitivity and equivalent specificity. Overall, DWI performed better than ¹⁸F-FDG PET/CT for preoperative N-staging in GC. When the efficacy of MDCT was taken as a reference, DWI represented a complementary imaging technique, while ¹⁸F-FDG PET/CT had limited utility for preoperative N-staging.

Correlations between the iodine concentrations from dual energy computed tomography and molecular markers Ki-67 and HIF-1α in rectal cancer: A preliminary study

PURPOSE

To investigate whether dual energy computed tomography (CT) with iodine quantification is correlated with molecular markers Ki-67and hypoxia-inducible factor 1α (HIF-1α)in rectal cancer (RC).

MATERIALS AND METHODS

Eighty patients (43 males and 37 females) diagnosed with rectal cancer got pelvic contrast-enhanced CT scan with dual energy computed tomography before any anticancer treatment. Analyse the normalized iodine concentration (NIC) values and CT values at each energy level (40-140 keV) from the virtual monochromatic image of the primary lesions. The postoperative specimens of all 80 patients underwent Ki-67 and HIF-1α immunohistochemistry staining. By SPSS17.0 software package, we analyzed the correlations of NIC values and CT values at each energy level (40-140 keV) with Ki-67 and HIF-1α expression. The receiver operating characteristic (ROC) curves of these dual energy computed tomography parameters were calculated and the diagnostic value were assessed.

RESULTS

There was a weak positive correlation between NIC values and carcinoembryonic antigen level (r=0.246, P=0.028) in RC. Both the value and the level of Ki-67 expression were correlated positively with the NIC values (r=0.344, P=0.002 and r=0.248, P=0.026). HIF-1α expression was correlated positively with the NIC values of the RC (r=0.598, P<0.001). The best threshold values of NIC values in diagnosing the expression of HIF-1α was 0.5839. The sensitivity, 78%; specificity, 87%; PPV, 86%; NPV,79%;accuracy, 83%.

CONCLUSION

The NIC values on dual energy computed tomography may be used as a measurement of hypoxia in RC and determining the ability of tumor invasion noninvasively.

Impact of Different Analytic Approaches on the Analysis of the Breast Fibroglandular Tissue Using Diffusion Weighted Imaging

Purpose. This study investigated the impact of the different region of interest (ROI) approaches on measurement of apparent diffusion coefficient (ADC) values in the breast firbroglandular tissue (FT). Methods. Breast MR images of 38 women diagnosed with unilateral breast cancer were studied. Percent density (PD) and ADC were measured from the contralateral normal breast. Four different ROIs were used for ADC measurement. The measured PD and ADC were correlated. Results. Among the four ROIs, the manually placed small ROI on FT gave the highest mean ADC (ADC = 1839 ± 343 [×10⁻⁶ mm²/s]), while measurement from the whole breast gave the lowest mean ADC (ADC = 933 ± 383 [×10⁻⁶ mm²/s]). The ADC measured from the whole breast was highly correlated with PD with r = 0.95. In slice-to-slice comparison, the central slices with more FT had higher ADC values than the peripheral slices did, presumably due to less partial volume effect from fat. Conclusions. Our results indicated that the measured ADC heavily depends on the composition of breast tissue contained in the ROI used for the ADC measurements. Women with low breast density showing lower ADC values were most likely due to the partial volume effect of fatty tissues.

DWI for Assessment of Rectal Cancer Nodes After Chemoradiotherapy: Is the Absence of Nodes at DWI Proof of a Negative Nodal Status?

OBJECTIVE

When considering organ preservation in patients with rectal cancer with good tumor response, assessment of a node-negative status after chemoradiation therapy (CRT) is important. DWI is a very sensitive technique to detect nodes. The study aim was to test the hypothesis that the absence of nodes at DWI after CRT is concordant with a ypN0 status.

MATERIALS AND METHODS

A retrospective study was performed of 90 patients with rectal cancer treated with CRT followed by restaging MRI at 1.5 T, including DWI (highest b value, 1000 s/mm²). Two independent readers counted the number of nodes visible in the mesorectal compartment on DW images obtained after CRT. The number of nodes on DWI (0 vs ≥ 1) was compared with the number of metastatic nodes at histopathology or long-term clinical follow-up (yN0 vs yN-positive status).

RESULTS

Seventy-one patients had a yN0 status, and 19 had a yN-positive status. For 10 patients, no nodes were observed at DWI, which was concordant with a yN0 status in 100% of cases. In the other 61 patients with a yN0 status, the median number of nodes detected at DWI was three (range, 1-17 nodes). To differentiate between yN0 and yN-positive status, sensitivity was 100%, specificity was 14%, the positive predictive value was 24%, and the negative predictive value was 100%.

CONCLUSION

Although the absence of nodes at DWI is not a frequent finding, it appears to be a reliable predictor of yN0 status after CRT in patients with rectal cancer. DWI may thus be a helpful adjunct in assessing response after CRT and may help select patients for organ-saving treatment.