Rectal cancer: assessment of complete response to preoperative combined radiation therapy with chemotherapy--conventional MR volumetry versus diffusion-weighted MR imaging

China special issue on gastrointestinal tumors-Radiological features of pathological complete response in mismatch repair deficient colorectal cancer after neoadjuvant PD-1 blockade: A post hoc analysis of the PICC phase II trial

Neoadjuvant programmed cell death protein 1 (PD-1) blockade exhibits promising efficacy in patients with mismatch repair deficient (dMMR) colorectal cancer (CRC). However, discrepancies between radiological and histological findings have been reported in the PICC phase II trial (NCT03926338). Therefore, we strived to discern radiological features associated with pathological complete response (pCR) based on computed tomography (CT) images. Data were obtained from the PICC trial that included 36 tumors from 34 locally advanced dMMR CRC patients, who received neoadjuvant PD-1 blockade for 3 months. Among the 36 tumors, 28 (77.8%) tumors achieved pCR. There were no statistically significant differences in tumor longitudinal diameter, the percentage change in tumor longitudinal diameter from baseline, primary tumor sidedness, clinical stage, extramural venous invasion status, intratumoral calcification, peritumoral fat infiltration, intestinal fistula and tumor necrosis between the pCR and non-pCR tumors. Otherwise, tumors with pCR had smaller posttreatment tumor maximum thickness (median: 10 mm vs 13 mm, P = .004) and higher percentage decrease in tumor maximum thickness from baseline (52.9% vs 21.6%, P = .005) compared to non-pCR tumors. Additionally, a higher proportion of the absence of vascular sign (P = .003, odds ratio [OR] = 25.870 [95% CI, 1.357-493.110]), nodular sign (P < .001, OR = 189.000 [95% CI, 10.464-3413.803]) and extramural enhancement sign (P = .003, OR = 21.667 [2.848-164.830]) was observed in tumors with pCR. In conclusion, these CT-defined radiological features may have the potential to serve as valuable tools for clinicians in identifying patients who have achieved pCR after neoadjuvant PD-1 blockade, particularly in individuals who are willing to adopt a watch-and-wait strategy.

Feature selection based on unsupervised clustering evaluation for predicting neoadjuvant chemoradiation response for patients with locally advanced rectal cancer

Accurate response prediction allows for personalized cancer treatment of locally advanced rectal cancer (LARC) with neoadjuvant chemoradiation. In this work, we designed a convolutional neural network (CNN) feature extractor with switchable 3D and 2D convolutional kernels to extract deep learning features for response prediction. Compared with radiomics features, convolutional kernels may adaptively extract local or global image features from multi-modal MR sequences without the need of feature predefinition. We then developed an unsupervised clustering based evaluation method to improve the feature selection operation in the feature space formed by the combination of CNN features and radiomics features. While normal process of feature selection generally includes the operations of classifier training and classification execution, the process needs to be repeated many times after new feature combinations were found to evaluate the model performance, which incurs a significant time cost. To address this issue, we proposed a cost effective process to use a constructed unsupervised clustering analysis indicator to replace the classifier training process by indirectly evaluating the quality of new found feature combinations in feature selection process. We evaluated the proposed method using 43 LARC patients underwent neoadjuvant chemoradiation. Our prediction model achieved accuracy, area-under-curve (AUC), sensitivity and specificity of 0.852, 0.871, 0.868, and 0.735 respectively. Compared with traditional radiomics methods, the prediction models (AUC = 0.846) based on deep learning-based feature sets are significantly better than traditional radiomics methods (AUC = 0.714). The experiments also showed following findings: (1) the features with higher predictive power are mainly from high-order abstract features extracted by CNN on ADC images and T2 images; (2) both ADC_Radiomics and ADC_CNN features are more advantageous for predicting treatment responses than the radiomics and CNN features extracted from T2 images; (3) 3D CNN features are more effective than 2D CNN features in the treatment response prediction. The proposed unsupervised clustering indicator is feasible with low computational cost, which facilitates the discovery of valuable solutions by highlighting the correlation and complementarity between different types of features.

Development and multicenter validation of a multiparametric imaging model to predict treatment response in rectal cancer

OBJECTIVES

To develop and validate a multiparametric model to predict neoadjuvant treatment response in rectal cancer at baseline using a heterogeneous multicenter MRI dataset.

METHODS

Baseline staging MRIs (T2W (T2-weighted)-MRI, diffusion-weighted imaging (DWI) / apparent diffusion coefficient (ADC)) of 509 patients (9 centres) treated with neoadjuvant chemoradiotherapy (CRT) were collected. Response was defined as (1) complete versus incomplete response, or (2) good (Mandard tumor regression grade (TRG) 1-2) versus poor response (TRG3-5). Prediction models were developed using combinations of the following variable groups: (1) Non-imaging: age/sex/tumor-location/tumor-morphology/CRT-surgery interval (2) Basic staging: cT-stage/cN-stage/mesorectal fascia involvement, derived from (2a) original staging reports, or (2b) expert re-evaluation (3) Advanced staging: variables from 2b combined with cTN-substaging/invasion depth/extramural vascular invasion/tumor length (4) Quantitative imaging: tumour volume + first-order histogram features (from T2W-MRI and DWI/ADC) Models were developed with data from 6 centers (n = 412) using logistic regression with the Least Absolute Shrinkage and Selector Operator (LASSO) feature selection, internally validated using repeated (n = 100) random hold-out validation, and externally validated using data from 3 centers (n = 97).

RESULTS

After external validation, the best model (including non-imaging and advanced staging variables) achieved an area under the curve of 0.60 (95%CI=0.48-0.72) to predict complete response and 0.65 (95%CI=0.53-0.76) to predict a good response. Quantitative variables did not improve model performance. Basic staging variables consistently achieved lower performance compared to advanced staging variables.

CONCLUSIONS

Overall model performance was moderate. Best results were obtained using advanced staging variables, highlighting the importance of good-quality staging according to current guidelines. Quantitative imaging features had no added value (in this heterogeneous dataset).

CLINICAL RELEVANCE STATEMENT

Predicting tumour response at baseline could aid in tailoring neoadjuvant therapies for rectal cancer. This study shows that image-based prediction models are promising, though are negatively affected by variations in staging quality and MRI acquisition, urging the need for harmonization.

KEY POINTS

This multicenter study combining clinical information and features derived from MRI rendered disappointing performance to predict response to neoadjuvant treatment in rectal cancer. Best results were obtained with the combination of clinical baseline information and state-of-the-art image-based staging variables, highlighting the importance of good quality staging according to current guidelines and staging templates. No added value was found for quantitative imaging features in this multicenter retrospective study. This is likely related to acquisition variations, which is a major problem for feature reproducibility and thus model generalizability.

Sense and non-sense of imaging in the era of organ preservation for rectal cancer

This review summarizes the current applications and benefits of imaging modalities for organ preservation in the treatment of rectal cancer. The concept of organ preservation in the treatment of rectal cancer has revolutionized the way rectal cancer is managed. Initially, organ preservation was limited to patients with locally advanced rectal cancer who needed neoadjuvant therapy to reduce tumor size before surgery and achieved complete response. However, neoadjuvant therapy is now increasingly utilized for smaller and less aggressive tumors to achieve primary organ preservation. Additionally, more intensive neoadjuvant strategies are employed to improve complete response rates and increase the chances of successful organ preservation. The selection of patients for organ preservation is a critical component of treatment, and imaging techniques such as digital rectal exam, endoscopy, and MRI are commonly used for this purpose. In this review, we provide an overview of what imaging modalities should be chosen and how they can aid in the selection and follow-up of patients undergoing organ-preserving strategies.

Association between Dynamic Contrast-Enhanced MRI Parameters and Prognostic Factors in Patients with Primary Rectal Cancer

BACKGROUND

To evaluate the association between perfusion parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with prognostic factors in primary rectal cancer patients.

METHODS

A sample of 51 patients with pathologically proven rectal adenocarcinoma through surgery were retrospectively enrolled. All the patients underwent preoperative DCE-MRI including 3D-spoiled gradient echo. Two radiologists determined the tumor border after radiologic-pathologic correlation and drew regions of interest. The perfusion parameters, including the volume transfer constant (K^trans), were calculated under the extended Toft model. The prognostic factors included TN stage, circumferential resection margin, extramural venous invasion, Kirsten-ras mutation, tumor size, carcinoembryonic antigen, and tumor differentiation. The association was assessed via correlation or t-test. For significant prognostic factors, receiver operating characteristic (ROC) curve analyses were performed to estimate the diagnostic predictive values.

RESULTS

K^trans only showed a significant difference according to tumor differentiation, between the well-differentiated (n = 6) and moderately differentiated (n = 45) groups (0.127 ± 0.032, 0.084 ± 0.036, p = 0.036). The AUC was 0.838 (95% CI, 0.702-0.929), and the estimated accuracy, sensitivity, and specificity were 87%, 90%, and 60%, respectively.

CONCLUSIONS

K^trans showed a significant difference based on tumor differentiation, which may be conducive to prediction of prognosis in primary rectal cancer.

Rectal MRI Interpretation After Neoadjuvant Therapy

In recent years, several key advances in the management of locally advanced rectal cancer have been made, including the implementation of total mesorectal excision as the standard surgical approach; use of neoadjuvant chemoradiotherapy in selected patients with a high risk of local recurrence, and finally, adoption of organ preservation strategies, through either local excision or nonoperative management in selected patients with clinical complete response following neoadjuvant chemoradiotherapy. This review aims to shed light on the role of rectal MRI in the assessment of treatment response after neoadjuvant therapy, which is especially important given the growing feasibility of nonoperative management. First, an overview of current neoadjuvant therapies and response assessment based on digital rectal examination, endoscopy, and MRI will be provided. Second, the use of a high-quality restaging rectal MRI protocol will be presented. Third, a step-by-step approach to assessing treatment response on restaging rectal MRI following neoadjuvant treatment will be outlined, acknowledging challenges faced by radiologists during MRI interpretation. Finally, research related to response assessment will be discussed. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 3.

MRI VS. FDG-PET for diagnosis of response to neoadjuvant therapy in patients with locally advanced rectal cancer

Aim

In this study, we aimed to compare the diagnostic values of MRI and FDG-PET for the prediction of the response to neoadjuvant chemoradiotherapy (NACT) of patients with locally advanced Rectal cancer (RC).

Methods

Electronic databases, including PubMed, Embase, and the Cochrane library, were systematically searched through December 2021 for studies that investigated the diagnostic value of MRI and FDG-PET in the prediction of the response of patients with locally advanced RC to NACT. The quality of the included studies was assessed using QUADAS. The pooled sensitivity, specificity, positive and negative likelihood ratio (PLR and NLR), and the area under the ROC (AUC) of MRI and FDG-PET were calculated using a bivariate generalized linear mixed model, random-effects model, and hierarchical regression.

Results

A total number of 74 studies with recruited 4,105 locally advanced RC patients were included in this analysis. The pooled sensitivity, specificity, PLR, NLR, and AUC for MRI were 0.83 (95% CI: 0.77-0.88), 0.85 (95% CI: 0.79-0.89), 5.50 (95% CI: 4.11-7.35), 0.20 (95% CI: 0.14-0.27), and 0.91 (95% CI: 0.88-0.93), respectively. The summary sensitivity, specificity, PLR, NLR and AUC for FDG-PET were 0.81 (95% CI: 0.77-0.85), 0.75 (95% CI: 0.70-0.80), 3.29 (95% CI: 2.64-4.10), 0.25 (95% CI: 0.20-0.31), and 0.85 (95% CI: 0.82-0.88), respectively. Moreover, there were no significant differences between MRI and FDG-PET in sensitivity (P = 0.565), and NLR (P = 0.268), while the specificity (P = 0.006), PLR (P = 0.006), and AUC (P = 0.003) of MRI was higher than FDG-PET.

Conclusions

MRI might superior than FGD-PET for the prediction of the response of patients with locally advanced RC to NACT.

Radiomics of locally advanced rectal cancer: machine learning-based prediction of response to neoadjuvant chemoradiotherapy using pre-treatment sagittal T2-weighted MRI

PURPOSE

Variable response to neoadjuvant chemoradiotherapy (nCRT) is observed among individuals with locally advanced rectal cancer (LARC), having a significant impact on patient management. In this work, we aimed to investigate the potential value of machine learning (ML)-based magnetic resonance imaging (MRI) radiomics in predicting therapeutic response to nCRT in patients with LARC.

MATERIALS AND METHODS

Seventy-six patients with LARC were included in this retrospective study. Radiomic features were extracted from pre-treatment sagittal T2-weighted MRI images, with 3D segmentation. Dimension reduction was performed with a reliability analysis, pair-wise correlation analysis, analysis of variance, recursive feature elimination, Kruskal-Wallis, and Relief methods. Models were created using four different algorithms. In addition to radiomic models, clinical only and different combined models were developed and compared. The reference standard was tumor regression grade (TRG) based on the Modified Ryan Scheme (TRG 0 vs TRG 1-3). Models were compared based on net reclassification index (NRI). Clinical utility was assessed with decision curve analysis (DCA).

RESULTS

Number of features with excellent reliability is 106. The best result was achieved with radiomic only model using eight features. The area under the curve (AUC), accuracy, sensitivity, and specificity for validation were 0.753 (standard deviation [SD], 0.082), 81.1%, 83.8%, and 75.0%; for testing, 0.705 (SD, 0.145), 73.9%, 81.2%, and 57.1%, respectively. Based on the clinical only model as reference, NRI for radiomic only model was the best. DCA also showed better clinical utility for radiomic only model.

CONCLUSIONS

ML-based T2-weighted MRI radiomics might have a potential in predicting response to nCRT in patients with LARC.

Comparison of the diagnostic performance of changes in signal intensity and volume from multiparametric MRI for assessing response of rectal cancer to neoadjuvant chemoradiotherapy

AIM

To evaluate the change in signal intensity (SI) and volume (V) from multiparametric magnetic resonance imaging (MRI) for assessing the response of locally advanced rectal cancer (LARC) to chemoradiotherapy (CRT).

MATERIALS AND METHODS

Eight-two LARC patients who underwent pre- and post-CRT T2-weighted (T2W), apparent diffusion coefficient (ADC), and contrast-enhanced T1-weighted (ceT1W) MRI were retrospectively analyzed. The change of volume (%△V) and relative SI ratio (%△SIR) from each sequence were determined. All LARCs were confirmed pathologically and classified as tumor regression grade (TRG) -0, 1, 2,or 3. Descriptive statistics and receiver operating characteristic (ROC) analysis, with calculation of area under the curve (AUC), were used to compare the diagnostic performances.

RESULTS

Sixteen patients had TRG-0, 15 had TRG-1, 35 had TRG-2, and 16 had TRG-3. Except for ADC-%△SIR, the remaining %△V and %△SIR values on MR sequences had significant differences among the four groups. The %△V and %△SIR (alone or together) did not distinguish TRG-1 from TRG-2, nor TRG-2 from TRG-3; however, differences between other TRGs were identified by %△V and %△SIR. The combined use of ADC-%△V and T2W-%△SIR provided the best diagnostic performance in distinguishing of TRG-0 from TRG-2 (AUC: 0.954) and from TRG-3 (AUC: 1.000).

CONCLUSIONS

Preoperative MRI of LARC patients after CRT has high diagnostic value for determination TRG, and may therefore improve the selection of patients most suitable for surgery.

Predicting neoadjuvant chemoradiotherapy response with functional imaging and liquid biomarkers in locally advanced rectal cancer

INTRODUCTION

Non-invasive predictive quantitative biomarkers are required to guide treatment individualization in patients with locally advanced rectal cancer (LARC) in order to maximise therapeutic outcomes and minimise treatment toxicity. Magnetic resonance imaging (MRI), positron emission tomography (PET) and blood biomarkers have the potential to predict chemoradiotherapy (CRT) response in LARC.

AREAS COVERED

This review examines the value of functional imaging (MRI and PET) and liquid biomarkers (circulating tumor cells (CTCs) and circulating tumor nucleic acid (ctNA)) in the prediction of CRT response in LARC. Selected imaging and liquid biomarker studies are presented and the current status of the most promising imaging (apparent diffusion co-efficient (ADC), K^trans, SUV_max, metabolic tumor volume (MTV) and total lesion glycolysis (TLG) and liquid biomarkers (circulating tumor cells (CTCs), circulating tumor nucleic acid (ctNA)) is discussed. The potential applications of imaging and liquid biomarkers for treatment stratification and a pathway to clinical translation are presented.

EXPERT OPINION

Functional imaging and liquid biomarkers provide novel ways of predicting CRT response. The clinical and technical validation of the most promising imaging and liquid biopsy biomarkers in multi-centre studies with harmonised acquisition techniques is required. This will enable clinical trials to investigate treatment escalation or de-escalation pathways in rectal cancer.

Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer

BACKGROUND

Whole-tumor apparent diffusion coefficient (ADC) histogram analysis is relevant to predicting the neoadjuvant chemoradiation therapy (nCRT) response in patients with locally advanced rectal cancer (LARC).

AIM

To evaluate the performance of ADC histogram-derived parameters for predicting the outcomes of patients with LARC.

METHODS

This is a single-center, retrospective study, which included 48 patients with LARC. All patients underwent a pre-treatment magnetic resonance imaging (MRI) scan for primary tumor staging and a second restaging MRI for response evaluation. The sample was distributed as follows: 18 responder patients (R) and 30 non-responders (non-R). Eight parameters derived from the whole-lesion histogram analysis (ADCmean, skewness, kurtosis, and ADC10^th, 25^th, 50^th, 75^th, 90^th percentiles), as well as the ADCmean from the hot spot region of interest (ROI), were calculated for each patient before and after treatment. Then all data were compared between R and non-R using the Mann-Whitney U test. Two measures of diagnostic accuracy were applied: the receiver operating characteristic curve and the diagnostic odds ratio (DOR). We also reported intra- and interobserver variability by calculating the intraclass correlation coefficient (ICC).

RESULTS

Post-nCRT kurtosis, as well as post-nCRT skewness, were significantly lower in R than in non-R (both P < 0.001, respectively). We also found that, after treatment, R had a larger loss of both kurtosis and skewness than non-R (∆%kurtosis and ∆skewness, P < 0.001). Other parameters that demonstrated changes between groups were post-nCRT ADC10^th, ∆%ADC10^th, ∆%ADCmean, and ROI ∆%ADCmean. However, the best diagnostic performance was achieved by ∆%kurtosis at a threshold of 11.85% (Area under the receiver operating characteristic curve [AUC] = 0.991, DOR = 376), followed by post-nCRT kurtosis = 0.78 × 10^-3 mm²/s (AUC = 0.985, DOR = 375.3), ∆skewness = 0.16 (AUC = 0.885, DOR = 192.2) and post-nCRT skewness = 1.59 × 10^-3 mm²/s (AUC = 0.815, DOR = 168.6). Finally, intraclass correlation coefficient analysis showed excellent intraobserver and interobserver agreement, ensuring the implementation of histogram analysis into routine clinical practice.

CONCLUSION

Whole-tumor ADC histogram parameters, particularly kurtosis and skewness, are relevant biomarkers for predicting the nCRT response in LARC. Both parameters appear to be more reliable than ADCmean from one-slice ROI.

A new magnetic resonance imaging tumour response grading scheme for locally advanced rectal cancer

BACKGROUND

The potential of using magnetic resonance image tumour-regression grading (MRI-TRG) system to predict pathological TRG is debatable for locally advanced rectal cancer treated by neoadjuvant radiochemotherapy.

METHODS

Referring to the American Joint Committee on Cancer/College of American Pathologists (AJCC/CAP) TRG classification scheme, a new four-category MRI-TRG system based on the volumetric analysis of the residual tumour and radiochemotherapy induced anorectal fibrosis was established. The agreement between them was evaluated by Kendall's tau-b test, while Kaplan-Meier analysis was used to calculate survival outcomes.

RESULTS

In total, 1033 patients were included. Good agreement between MRI-TRG and AJCC/CAP TRG classifications was observed (k = 0.671). Particularly, as compared with other pairs, MRI-TRG 0 displayed the highest sensitivity [90.1% (95% CI: 84.3-93.9)] and specificity [92.8% (95% CI: 90.4-94.7)] in identifying AJCC/CAP TRG 0 category patients. Except for the survival ratios that were comparable between the MRI-TRG 0 and MRI-TRG 1 categories, any two of the four categories had distinguished 3-year prognosis (all P < 0.05). Cox regression analysis further proved that the MRI-TRG system was an independent prognostic factor (all P < 0.05).

CONCLUSION

The new MRI-TRG system might be a surrogate for AJCC/CAP TRG classification scheme. Importantly, the system is a reliable and non-invasive way to identify patients with complete pathological responses.

Complete Response Evaluation of Locally Advanced Rectal Cancer to Neoadjuvant Chemoradiotherapy Using Textural Features Obtained from T2 Weighted Imaging and ADC Maps

BACKGROUND

The prediction of pathological responses for locally advanced rectal cancer using magnetic resonance imaging (MRI) after neoadjuvant chemoradiotherapy (CRT) is a challenging task for radiologists, as residual tumor cells can be mistaken for fibrosis. Texture analysis of MR images has been proposed to understand the underlying pathology.

OBJECTIVE

This study aimed to assess the responses of lesions to CRT in patients with locally advanced rectal cancer using the first-order textural features of MRI T2-weighted imaging (T2-WI) and apparent diffusion coefficient (ADC) maps.

METHODS

Forty-four patients with locally advanced rectal cancer (median age: 57 years) who underwent MRI before and after CRT were enrolled in this retrospective study. The first-order textural parameters of tumors on T2-WI and ADC maps were extracted. The textural features of lesions in pathologic complete responders were compared to partial responders using Student's t- or Mann-Whitney U tests. A comparison of textural features before and after CRT for each group was performed using the Wilcoxon rank sum test. Receiver operating characteristic curves were calculated to detect the diagnostic performance of the ADC.

RESULTS

Of the 44 patients evaluated, 22 (50%) were placed in a partial response group and 50% were placed in a complete response group. The ADC changes of the complete responders were statistically more significant than those of the partial responders (P = 0.002). Pathologic total response was predicted with an ADC cut-off of 1310 x 10-6 mm2/s, with a sensitivity of 72%, a specificity of 77%, and an accuracy of 78.1% after neoadjuvant CRT. The skewness of the T2-WI before and after neoadjuvant CRT showed a significant difference in the complete response group compared to the partial response group (P = 0.001 for complete responders vs. P = 0.482 for partial responders). Also, relative T2-WI signal intensity in the complete response group was statistically lower than that of the partial response group after neoadjuvant CRT (P = 0.006).

CONCLUSION

As a result of the conversion of tumor cells to fibrosis, the skewness of the T2-WI before and after neoadjuvant CRT was statistically different in the complete response group compared to the partial response group, and the complete response group showed statistically lower relative T2-WI signal intensity than the partial response group after neoadjuvant CRT. Additionally, the ADC cut-off value of 1310 × 10-6 mm2/s could be used as a marker for complete response along with absolute ADC value changes within this dataset.

[Complete response after neoadjuvant therapy: how certain is radiology?]

The concept of total neoadjuvant therapy (TNT) means a paradigm shift in the treatment of patients with rectal cancer. In cases in which the TNT induced a complete clinical response (cCR), an organ preserving watch and wait therapy concept can now be provided more often; however, this increases the demand for imaging for the determination of cCR and in the subsequent follow-up. In this article, the performance of radiology in these scenarios will be evaluated and discussed. Magnetic resonance imaging (MRI) is the current standard for local assessment of the rectum with a high sensitivity for diagnosis and staging of rectal cancer, residual tumor and tumor recurrence. However, the certain exclusion of residual malignant tissue is still difficult, in particular the differentiation of residual scar tissue from vital residual tumor is only possible with low specificity and a moderate negative predictive value (NPV). The currently discussed criteria for the assessment of imaging have not yet been validated in large cohorts and are frequently subjective. An improvement of the diagnostic accuracy for identification of cCR in patients after TNT and for monitoring patients in watch and wait treatment concepts can certainly be achieved by the integration of MRI, endoscopy and endosonography as well as clinical parameters. This should enable for identification of patients with an incomplete response or local recurrence, in time for extended treatment to be initiated without relevant impact on the patient outcome.

Diagnostic performance of MRI and endoscopy for assessing complete response in rectal cancer after neoadjuvant chemoradiotherapy: a systematic review of the literature

BACKGROUND

The diagnostic performance of magnetic resonance imaging (MRI) modalities and/or endoscopy for assessing complete response in rectal cancer after neoadjuvant chemoradiotherapy (nCRT) is unclear.

PURPOSE

To summarize existing evidence on the diagnostic performance of diffusion-weighted MRI, perfusion-weighted MRI, T2-weighted MR tumor regression grade, and/or endoscopy for assessing complete tumor response after nCRT.

MATERIAL AND METHODS

MEDLINE and Embase databases were searched. The PRISMA guidelines were followed. Sensitivity, specificity, negative predictive, and positive predictive values were retrieved from included studies.

RESULTS

In total, 81 studies were eligible for inclusion. Evidence suggests that combined use of MRI and endoscopy tends to improve the diagnostic performance compared to single imaging modality. The positive predictive value of a complete response varies substantially between studies. There is considerable heterogeneity between studies.

CONCLUSION

Combined re-staging tends to improve diagnostic performance compared to single imaging modality, but the vast majority of studies fail to offer true clinical value due to the study heterogeneity.

MRI-based delta-radiomics are predictive of pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer

RATIONALE AND OBJECTIVES

To investigate the capability of delta-radiomics to predict pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).

MATERIALS AND METHODS

This retrospective study enrolled 165 consecutive patients with LARC (training set, n = 116; test set, n = 49) who received nCRT before surgery. All patients underwent pre- and post-nCRT MRI examination from which radiomics features were extracted. A delta-radiomics feature was defined as the percentage change in a radiomics feature from pre- to post-nCRT MRI. A data reduction and feature selection process including the least absolute shrinkage and selection operator algorithm was performed for building T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) delta-radiomics signature. Logistic regression was used to build a T2WI and DWI combined radiomics model. Receiver operating characteristic analysis was performed to assess diagnostic performance. Delong method was used to compare the performance of delta-radiomics model with that of magnetic resonance tumor regression grade (mrTRG).

RESULTS

Twenty-seven of 165 patients (16.4%) achieved pCR. T2WI and DWI delta-radiomics signature, and the combined model showed good predictive performance for pCR. The combined model achieved the highest areas under the receiver operating characteristic curves of 0.91 (95% confidence interval: 0.85-0.98) and 0.91 (95% confidence interval: 0.83-0.99) in the training and test sets, respectively (significantly greater than those for mrTRG; training set, p < 0.001; test set, p = 0.04).

CONCLUSION

MRI-based delta-radiomics can help predict pCR after nCRT in patients with LARC with better performance than mrTRG.

Diffusion kurtosis imaging-derived histogram metrics for prediction of resistance to neoadjuvant chemoradiotherapy in rectal adenocarcinoma: Preliminary findings

PURPOSE

This study aimed to evaluate the potential role of diffusion kurtosis imaging (DKI)-derived parameters for assessing resistance to CRT in patients with Locally advanced rectal cancer (LARC) by using histogram analysis derived from whole-tumor volumes.

METHOD

136 consecutive patients with histologically confirmed rectal adenocarcinoma who underwent MRI examination before and after chemoradiotherapy were enrolled in our retrospective study. The parameters D, K, and conventional apparent diffusion coefficient (ADC) were measured using whole-tumor volume histogram analysis. The AJCC tumor regression grading (TRG) system was the standard reference (resistance: TRG 3; non-resistance: TRG 0-2). Receiver operating characteristic (ROC) curves were used for evaluating the diagnostic performance.

RESULTS

Aside from the skew and kurtosis values, we found all the histogram metrics of D and ADC values significantly increased after CRT (all p < 0.001). In contrast, the histogram metrics of K values significantly decreased after CRT. The majority of percentiles metrics of D, K, and ADC values were correlated with tumor resistance before and after CRT (P < 0.05), except for the skew and kurtosis values. Regarding the comparison of the diagnostic performance of all the histogram metrics, the percentage D_mean change (ΔD_mean) showed the highest AUC value of 0.939, and the corresponding sensitivity, specificity, PPV, and NPV were 84.1% and 94.6%, 88.1% and 92.6%, respectively.

CONCLUSIONS

These preliminary results demonstrated that DKI-derived histogram metrics, especially the pre-treatment metrics and ΔD_mean, were useful to assess tumoral resistance to CRT and individual clinical management for patients with LARC.

Clinical outcome of neoadjuvant chemoradiation in rectal cancer treatment

To determine the clinical and pathological outcome of locally advanced rectal cancer patients treated with neoadjuvant chemoradiation (chemoradiotherapy [CRT]) followed by curative surgery and to identify predictive factors of pathological complete response (pCR).Locally advanced rectal cancer patients undergoing CRT followed by curative surgery from January 2012 to December 2017 were included. Patient's demographic data, pretreatment tumor characteristics, type of CRT regimens, type of surgery, postoperative complications, pathological reports and follow up records were analyzed. Univariate and multivariate analyses were applied to identify predictive factors for pCR. Five-year disease free and overall survival were estimated by Kaplan-Meier method and compared between pCR and non-pCR groups.A total of 85 patients were analyzed. Eighteen patients (21.1%) achieved pCR. The sphincter-saving surgery rate was 57.6%. After univariate analyses, tumor length >4 cm (P = .007) and positive lymph nodes (P = .040) were significantly associated with decreased rate of pCR. Complete clinical response was significantly associated with higher rate of pCR (P = .015). Multivariate analyses demonstrated that tumor length >4 cm (P = .010) was significantly associated with decreased rate of pCR. After a median follow-up of 65 months (IQR 34-79), the calculated 5-year overall survival and disease-free survival rates were 81.4% and 69.7%, respectively. Patients who achieved pCR tend to had longer 5-year disease-free survival (P = .355) and overall survival (P = .361) than those who did not.Tumor length >4 cm was associated with decreased rate of pCR in locally advanced rectal cancer who had CRT followed by surgery. Longer waiting time or more intense adjuvant treatment may be considered to improved pCR and oncological outcomes.

Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.

Re-staging and follow-up of rectal cancer patients with MR imaging when "Watch-and-Wait" is an option: a practical guide

In the past nearly 20 years, organ-sparing when no apparent viable tumour is present after neoadjuvant therapy has taken an increasingly relevant role in the therapeutic management of locally-advanced rectal cancer patients. The decision to include a patient or not in a “Watch-and-Wait” program relies mainly on endoscopic assessment by skilled surgeons, and MR imaging by experienced radiologists. Strict surveillance using the same modalities is required, given the chance of a local regrowth is of approximately 25–30%, almost always surgically salvageable if caught early. Local regrowths occur at the endoluminal aspect of the primary tumour bed in almost 90% of patients, but the rest are deep within it or outside the rectal wall, in which case detection relies solely on MR Imaging. In this educational review, we provide a practical guide for radiologists who are, or intend to be, involved in the re-staging and follow-up of rectal cancer patients in institutions with an established “Watch-and-Wait” program. First, we discuss patient preparation and MR imaging acquisition technique. Second, we focus on the re-staging MR imaging examination and review the imaging findings that allow us to assess response. Third, we focus on follow-up assessments of patients who defer surgery and confer about the early signs that may indicate a sustained/non-sustained complete response, a rectal/extra-rectal regrowth, and the particular prognosis of the “near-complete” responders. Finally, we discuss our proposed report template.

Predicting Treatment Response of Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Using Amide Proton Transfer MRI Combined With Diffusion-Weighted Imaging

Objective

To evaluate amide proton weighted (APTw) MRI combined with diffusion-weighted imaging (DWI) in predicting neoadjuvant chemoradiotherapy (NCRT) response in patients with locally advanced rectal cancer (LARC).

Methods

53 patients with LARC were enrolled in this retrospective study. MR examination including APTw MRI and DWI was performed before and after NCRT. APTw SI, ADC value, tumor size, CEA level before and after NCRT were assessed. The difference of the above parameters between before and after NCRT was calculated. The tumor regression grading (TRG) was assessed by American Joint Committee on Cancer’s Cancer Staging Manual AJCC 8th score. The Shapiro-Wilk test, paired t-test and Wilcoxon Signed Ranks test, two-sample t-test, Mann-Whitney U test and multivariate analysis were used for statistical analysis.

Results

Of the 53 patients, 19 had good responses (TRG 0-1), 34 had poor responses (TRG 2-3). After NCRT, all the rectal tumors demonstrated decreased APT values, increased ADC values, reduced tumor volumes and CEA levels (all p < 0.001). Good responders demonstrated higher pre-APT values, higher Δ APT values, lower pre- ADC values and higher Δ tumor volumes than poor responders. Pre-APT combined with pre-ADC achieved the best diagnostic performance, with AUC of 0.895 (sensitivity of 85.29%, specificity of 89.47%, p < 0.001) in predicting good response to NCRT.

Conclusion

The combination of APTw and DWI may serve as a noninvasive biomarker for evaluating and identifying response to NCRT in LARC patients.

Endometrial cancer: the role of MRI quantitative assessment in preoperative staging and risk stratification

BACKGROUND

New methods to reduce subjectivity in preoperative magnetic resonance imaging (MRI) staging of endometrial cancer are needed.

PURPOSE

To investigate the role of MRI quantitative assessment in staging and risk stratification of endometrial cancer.

MATERIAL AND METHODS

Preoperative T2-weighted (T2W) images and diffusion-weighted imaging of 42 patients were analyzed retrospectively by two radiologists. Tumor area ratio (TAR) and tumor volume ratio (TVRseg) were calculated by semi-automatic segmentation of the tumor and uterus on T2W imaging and apparent diffusion coefficient (ADC). TVR was also calculated by the 3D metric method (TVRmetric). Mean ADC_tumor was calculated. The patients were allocated to risk groups regarding the stage, grade, and lymphovascular invasion (LVI) status.

RESULTS

TAR, TVRmetric, T2W TVRseg, and ADC TVRseg showed a significant difference between the superficial and deep myometrial invasion groups (P < 0.001). All of these parameters showed a good diagnostic performance for detecting deep myometrial invasion (AUC>0.82), the highest accuracy rate (85%) was found with T2W TVRseg. LVI was significantly associated with TAR (P = 0.002) and T2W TVRseg (P = 0.014), while the cervical invasion was associated with TAR (P = 0.03). ADC_tumor was significantly lower in high-grade tumors (P = 0.002). There was a significant difference in ADC_tumor (P = 0.002), TAR (P = 0.004), and T2W TVRseg (P = 0.038) between the low- and high-risk groups. AUC of TAR and T2W TVRseg for detecting high-risk groups were 0.80 and 0.77, respectively, while AUC of ADC_tumor for the low-risk group was 0.75.

CONCLUSION

MRI quantitative assessments such as TAR, TVR, and ADC_tumor may improve the accuracy of preoperative staging and can help in risk stratification of endometrial cancer.

MRI Evaluation of Complete Response of Locally Advanced Rectal Cancer After Neoadjuvant Therapy: Current Status and Future Trends

Complete tumor response can be achieved in a certain proportion of patients with locally advanced rectal cancer, who achieve maximal response to neoadjuvant therapy (NAT). For these patients, a watch-and-wait (WW) or nonsurgical strategy has been proposed and is becoming widely practiced in order to avoid unnecessary surgical complications. Therefore, a non-invasive, reliable diagnostic tool for accurately evaluating complete tumor response is needed. Magnetic resonance imaging (MRI) plays a crucial role in both primary staging and restaging tumor response to NAT in rectal cancer without relying on resected specimen. In recent years, numerous efforts have been made to research the value of MRI in predicting and evaluating complete response in rectal cancer. Current MRI evaluation is mainly based on morphological and functional images. Morphologic MRI yields high soft tissue resolution, multiplanar images, and provides detailed depictions of rectal cancer and its surrounding structures. Functional MRI may help to distinguish residual tumor from fibrosis, therefore improving the diagnostic performance of morphologic MRI in identifying complete tumor response. Both morphologic and functional MRI have several promising parameters that may help accurately evaluate and/or predict complete response of rectal cancer. However, these parameters still have limitations and the results remain inconsistent. Recent development of new techniques, such as textural analysis, radiomics analysis and deep learning, demonstrate great potential based on MRI-derived parameters. This article aimed to review and help better understand the strengths, limitations, and future trends of these MRI-derived methods in evaluating complete response in rectal cancer.

T2-weighted, apparent diffusion coefficient and 18F-FDG PET histogram analysis of rectal cancer after preoperative chemoradiotherapy

Background

The aim of our study was to investigate the correlation among T2-weighted (T2w) images, apparent diffusion coefficient (ADC) maps, ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET) images, histogram analysis and the pathological response in locally advanced rectal cancer (LARC) after preoperative chemoradiotherapy (pCRT).

Methods

Patients with LARC were prospectively enrolled between February 2015 and August 2018 and underwent PET/magnetic resonance imaging (MRI). MRI included T2w and diffusion-weighted imaging (DWI)-sequences. ADC maps and PET images were matched to the T2w images. Voxel-based standardized uptake values (SUVs,) ADC and T2w-signal-intensity values were collected from the volumes of interest (VOIs) and mean, skewness and kurtosis were calculated. Spearman’s correlation coefficient was applied to evaluate the correlation among the variables and tumor regression grade (TRG), T stage, N stage and fibrosis.

Results

Twenty-two patients with biopsy-proven LARC in the low or mid rectum were enrolled [17 males, mean age was 69 years (range 49–85 years)]. Seven patients experienced complete regression (TRG1). A significant positive correlation was found between SUV mean values (ρ = 0.480; p = 0.037) and TRG. No other significant correlations were found.

Conclusions

Histogram analysis of SUV values is a predictor of TRG in LARC.

Evaluation of a multiparametric MRI scoring system for histopathologic treatment response following preoperative chemoradiotherapy for rectal cancer

PURPOSE

To evaluate the performance of a multiparametric (mp) MRI scoring system for assessment of tumour response in patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (CRT).

METHOD

Fifty-nine consecutive patients with LARC who had rectal MRI before and after CRT followed by surgery were included. Two radiologists retrospectively assessed tumour response using a proposed mpMRI scoring system. Treatment response was classified as complete, near complete, partial or poor. Accuracy, sensitivity, specificity, positive predictive value and negative predictive values were calculated and inter-reader agreements were assessed. Pathologic tumour regression grade (pTRG) was the reference standard.

RESULTS

Treatment response was correctly predicted by both readers in 32.2%-40.7% of patients. Overestimation was more common than underestimation. Sensitivity, specificity, PPV and NPV for pathologic complete response (pCR) among both readers was 16.7-33.0 %, 88.7-94.2 %, 14.3-40.0 % and 92.5-94.2 % respectively. Sensitivity and PPV for both readers improved to 56.0-60.0 % and 53.6-66.7 % respectively when complete response and near complete response categories (good responders) were combined. Inter-reader agreement using the scoring system was fair (κ = 0.383). Agreement between mpMRI score and pathological tumour response was poor to fair for both readers (κ = 0.050 to 0.258) but improved when complete and near complete response categories (good responders) were combined (κ = 0.214 to 0.362).

CONCLUSIONS

Despite low agreement between radiological tumour response and pTRG, the proposed mpMRI-based scoring system appears useful in identifying good responders who may benefit from nonoperative management strategies.

Comparison of percentage changes in quantitative diffusion parameters for assessing pathological complete response to neoadjuvant therapy in locally advanced rectal cancer: a meta-analysis

PURPOSE

To evaluate and compare the diagnostic performance of percentage changes in apparent diffusion coefficient (∆ADC%) and slow diffusion coefficient (∆D%) for assessing pathological complete response (pCR) to neoadjuvant therapy in patients with locally advanced rectal cancer (LARC).

METHODS

A systematic search in PubMed, EMBASE, the Web of Science, and the Cochrane Library was performed to retrieve related original studies. For each parameter (∆ADC% and ∆D%), we pooled the sensitivity, specificity and calculated the area under summary receiver operating characteristic curve (AUROC) values. Meta-regression and subgroup analyses were performed to explore heterogeneity among the studies on ∆ADC%.

RESULTS

15 original studies (804 patients with 805 lesions, 15 studies on ∆ADC%, 4 of the studies both on ∆ADC% and ∆D%) were included. pCR was observed in 213 lesions (26.46%). For the assessment of pCR, the pooled sensitivity, specificity and AUROC of ∆ADC% were 0.83 (95% confidence intervals [CI] 0.76, 0.89), 0.74 (95% CI 0.66, 0.81), 0.87 (95% CI 0.83, 0.89), and ∆D% were 0.70 (95% CI 0.52, 0.84), 0.81 (95% CI 0.65, 0.90), 0.81 (95% CI 0.77, 0.84), respectively. In the four studies on the both metrics, ∆ADC% yielded an equivalent diagnostic performance (AUROC 0.80 [95% CI 0.76, 0.83]) to ∆D%, but lower than in the studies (n = 11) only on ∆ADC% (AUROC 0.88 [95% CI 0.85, 0.91]). Meta-regression and subgroup analyses showed no significant factors affecting heterogeneity.

CONCLUSIONS

Our meta-analysis confirms that ∆ADC% could reliably evaluate pCR in patients with LARC after neoadjuvant therapy. ∆D% may not be superior to ∆ADC%, which deserves further investigation.

MRI radiomics in the prediction of therapeutic response to neoadjuvant therapy for locoregionally advanced rectal cancer: a systematic review

Introduction: The standard of care for locoregionally advanced rectal cancer is neoadjuvant therapy (NA CRT) prior to surgery, of which 10-30% experience a complete pathologic response (pCR). There has been interest in using imaging features, also known as radiomics features, to predict pCR and potentially avoid surgery. This systematic review aims to describe the spectrum of MRI studies examining high-performing radiomic features that predict NA CRT response.Areas covered: This article reviews the use of pre-therapy MRI in predicting NA CRT response for patients with locoregionally advanced rectal cancer (T3/T4 and/or N1+). The primary outcome was to identify MRI radiomic studies; secondary outcomes included the power and the frequency of use of radiomic features.Expert opinion: Advanced models incorporating multiple radiomics categories appear to be the most promising. However, there is a need for standardization across studies with regards to; the definition of NA CRT response, imaging protocols, and radiomics features incorporated. Further studies are needed to validate current radiomics models and to fully ascertain the value of MRI radiomics in the response prediction for locoregionally advanced rectal cancer.

Modern MR Imaging Technology in Rectal Cancer; There Is More Than Meets the Eye

MR imaging (MRI) is now part of the standard work up of patients with rectal cancer. Restaging MRI has been traditionally used to plan the surgical approach. Its role has recently increased and been adopted as a valuable tool to assist the clinical selection of clinical (near) complete responders for organ preserving treatment. Recently several studies have addressed new imaging biomarkers that combined with morphological provides a comprehensive picture of the tumor. Diffusion-weighted MRI (DWI) has entered the clinics and proven useful for response assessment after chemoradiotherapy. Other functional (quantitative) MRI technologies are on the horizon including artificial intelligence modeling. This narrative review provides an overview of recent advances in rectal cancer (re)staging by imaging with a specific focus on response prediction and evaluation of neoadjuvant treatment response. Furthermore, directions are given for future research.

The apparent diffusion coefficient is a useful biomarker in predicting treatment response in patients with locally advanced rectal cancer

Background

Apparent diffusion coefficient (ADC) values achieve promising results in treatment response prediction in patients with several types of cancers.

Purpose

To determine whether ADC values predict neoadjuvant chemoradiation treatment (nCRT) response in patients with locally advanced rectal cancer (LARC).

Material and Methods

Forty-four patients with LARC who underwent magnetic resonance imaging scans before and after nCRT followed by delayed surgery were enrolled retrospectively. The sample was distributed as follows: responders (R), n = 8; and non-responders (Non-R), n = 36. Three markers of treatment response were considered: post-nCRT measures; ΔADC; and Δ%ADC. Statistical analysis included a Wilcoxon test, a Mann–Whitney U test, and a receiver operating characteristic (ROC) analysis in order to evaluate the diagnostic accuracy for each ADC value marker to differentiate between R and Non-R.

Results

Both minimum and mean ADC values were significantly higher after nCRT in the R group, while non-significant differences between basal and control ADC values were found in the non-R group. In addition, ΔADC and Δ%ADC exhibited increased values after nCRT in R when compared with non-R. ROC analysis revealed the following diagnostic performance parameters: post-nCRT: ADC_min = 1.05 × 10⁻³ mm²/s (sensitivity 61.1% and specificity 66.7%), ADC_mean = 1.50 × 10⁻³ mm²/s (sensitivity 72.2% and specificity 83.3%), ΔADC: ADC_min = 0.35 (sensitivity 66.7% and specificity 83.3%), ADC_mean = 0.50 (sensitivity 72% and specificity 83%); and Δ%ADC: ADC_min = 44% (sensitivity 66.7% and specificity 83.3%) and ADC_mean = 60% (sensitivity 83% and specificity 99%).

Conclusion

Our findings suggest that post-treatment rectal tumor ADC values, as well changes between pre- and post-treatment values, may be biomarkers for predicting treatment response in patients with LARC who underwent nCRT.

Feasibility of Simultaneous Multislice Acceleration Technique in Diffusion-Weighted Magnetic Resonance Imaging of the Rectum

Objective

To assess the feasibility of simultaneous multislice-accelerated diffusion-weighted imaging (SMS-DWI) of the rectum in comparison with conventional DWI (C-DWI) in rectal cancer patients.

Materials and Methods

This study included 65 patients with initially-diagnosed rectal cancer. All patients underwent C-DWI and SMS-DWI with acceleration factors of 2 and 3 (SMS2-DWI and SMS3-DWI, respectively) using a 3T scanner. Acquisition times of the three DWI sequences were measured. Image quality in the three DWI sequences was reviewed by two independent radiologists using a 4-point Likert scale and subsequently compared using the Friedman test. Apparent diffusion coefficient (ADC) values for rectal cancer and the normal rectal wall were compared among the three sequences using repeated measures analysis of variance.

Results

Acquisition times using C-DWI, SMS2-DWI, and SMS3-DWI were 173 seconds, 107 seconds, (38.2% shorter than C-DWI), and 77 seconds (55.5% shorter than C-DWI), respectively. For all image quality parameters other than distortion (margin sharpness, artifact, lesion conspicuity, and overall image quality), C-DWI and SMS2-DWI yielded better results than did SMS3-DWI (Ps < 0.001), with no significant differences observed between C-DWI and SMS2-DWI (Ps ≥ 0.054). ADC values of rectal cancer (p = 0.943) and normal rectal wall (p = 0.360) were not significantly different among C-DWI, SMS2-DWI, and SMS3-DWI.

Conclusion

SMS-DWI using an acceleration factor of 2 is feasible for rectal MRI resulting in substantial reductions in acquisition time while maintaining diagnostic image quality and similar ADC values to those of C-DWI.

Watch and wait approach in rectal cancer: Current controversies and future directions

According to the main international clinical guidelines, the recommended treatment for locally-advanced rectal cancer is neoadjuvant chemoradiotherapy followed by surgery. However, doubts have been raised about the appropriate definition of clinical complete response (cCR) after neoadjuvant therapy and the role of surgery in patients who achieve a cCR. Surgical resection is associated with significant morbidity and decreased quality of life (QoL), which is especially relevant given the favourable prognosis in this patient subset. Accordingly, there has been a growing interest in alternative approaches with less morbidity, including the organ-preserving watch and wait strategy, in which surgery is omitted in patients who have achieved a cCR. These patients are managed with a specific follow-up protocol to ensure adequate cancer control, including the early identification of recurrent disease. However, there are several open questions about this strategy, including patient selection, the clinical and radiological criteria to accurately determine cCR, the duration of neoadjuvant treatment, the role of dose intensification (chemotherapy and/or radiotherapy), optimal follow-up protocols, and the future perspectives of this approach. In the present review, we summarize the available evidence on the watch and wait strategy in this clinical scenario, including ongoing clinical trials, QoL in these patients, and the controversies surrounding this treatment approach.

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).

MRI prediction of pathological response in locally advanced rectal cancer: when apparent diffusion coefficient radiomics meets conventional volumetry

AIM

To investigate the role of diffusion-weighted imaging (DWI), T2-weighted (W) imaging, and apparent diffusion coefficient (ADC) histogram analysis before, during, and after neoadjuvant chemoradiotherapy (CRT) in the prediction of pathological response in patients with locally advanced rectal cancer (LARC).

MATERIALS AND METHODS

Magnetic resonance imaging (MRI) at 1.5 T was performed in 43 patients with LARC before, during, and after CRT. Tumour volume was measured on both T2-weighted (V_T2W) and on DWI at b=1,000 images (V_b,1,000) at each time point, hence the tumour volume reduction rate (ΔV_T2W and ΔV_b,1,000) was calculated. Whole-lesion (three-dimensional [3D]) first-order texture analysis of the ADC map was performed. Imaging parameters were compared to the pathological tumour regression grade (TRG). The diagnostic performance of each parameter in the identification of complete responders (CR; TRG4), partial responders (PR; TRG3) and non-responders (NR; TRG0-2) was evaluated by multinomial regression analysis and receiver operating characteristics curves.

RESULTS

After surgery, 11 patients were CR, 22 PR, and 10 NR. Before CRT, predictions of CR resulted in an ADC value of the 75th percentile and median, with good accuracy (74% and 86%, respectively) and sensitivity (73% and 82%, respectively). During CRT, the best predictor of CR was ΔV_T2W (-58.3%) with good accuracy (81%) and excellent sensitivity (91%). After CRT, the best predictors of CR were ΔV_T2W (-82.8%) and ΔV_{b, 1,000} (-86.8%), with 84% accuracy in both cases and 82% and 91% sensitivity, respectively.

CONCLUSIONS

The median ADC value at pre-treatment MRI and ΔV_T2W (from pre-to-during CRT MRI) may have a role in early and accurate prediction of response to treatment. Both ΔV_T2W and ΔV_b,1,000 (from pre-to-post CRT) can help in the identification of CR after CRT.

Exploring MR regression patterns in rectal cancer during neoadjuvant radiochemotherapy with daily T2- and diffusion-weighted MRI

Background

To date, only limited magnetic resonance imaging (MRI) data are available concerning tumor regression during neoadjuvant radiochemotherapy (RCT) of rectal cancer patients, which is a prerequisite for adaptive radiotherapy (RT) concepts. This exploratory study prospectively evaluated daily fractional MRI during neoadjuvant treatment to analyze the predictive value of MR biomarkers for treatment response.

Methods

Locally advanced rectal cancer patients were examined with daily MRI during neoadjuvant RCT. Contouring of the tumor volume was performed for each MRI scan by using T2- and diffusion-weighted-imaging (DWI)-sequences. The daily apparent-diffusion coefficient (ADC) was calculated. Volumetric and functional tumor changes during RCT were analyzed and correlated with the pathological response after surgical resection.

Results

In total, 171 MRI scans of eight patients were analyzed regarding anatomical and functional dynamics during RCT. Pathological complete response (pCR) could be achieved in four patients, and four patients had a pathological partial response (pPR) following neoadjuvant treatment. T2- and DWI-based volumetry proved to be statistically significant in terms of therapeutic response, and volumetric thresholds at week two and week four during RCT were defined for the prediction of pCR. In contrast, the average tumor ADC values widely overlapped between both response groups during RCT and appeared inadequate to predict treatment response in our patient cohort.

Conclusion

This prospective exploratory study supports the hypothesis that MRI may be able to predict pCR of rectal cancers early during neoadjuvant RCT. Our data therefore provide a useful template to tailor future MR-guided adaptive treatment concepts.

Response Assessment with MRI after Chemoradiotherapy in Rectal Cancer: Current Evidences

Baseline magnetic resonance imaging (MRI) has become the primary staging modality for surgical plans and stratification of patient populations for more efficient neoadjuvant treatment. Patients who exhibit a complete response to chemoradiotherapy (CRT) may achieve excellent local tumor control and better quality of life with organ-preserving treatments such as local excision or even watch-and-wait management. Therefore, the evaluation of tumor response is a key factor for determining the appropriate treatment following CRT. Although post-CRT MRI is generally accepted as the first-choice method for evaluating treatment response after CRT, its application in the clinical decision process is not fully validated. In this review, we will discuss various oncologic treatment options from radical surgical technique to organ-preservation strategies for achieving better cancer control and improved quality of life following CRT. In addition, the current status of post-CRT MRI in restaging rectal cancer as well as the main imaging features that should be evaluated for treatment planning will also be described for the tailored treatment.

Feasibility of multi-parametric magnetic resonance imaging combined with machine learning in the assessment of necrosis of osteosarcoma after neoadjuvant chemotherapy: a preliminary study

BACKGROUND

Response evaluation of neoadjuvant chemotherapy (NACT) in patients with osteosarcoma is significant for the termination of ineffective treatment, the development of postoperative chemotherapy regimens, and the prediction of prognosis. However, histological response and tumour necrosis rate can currently be evaluated only in resected specimens after NACT. A preoperatively accurate, noninvasive, and reproducible method of response assessment to NACT is required. In this study, the value of multi-parametric magnetic resonance imaging (MRI) combined with machine learning for assessment of tumour necrosis after NACT for osteosarcoma was investigated.

METHODS

Twelve patients with primary osteosarcoma of limbs underwent NACT and received MRI examination before surgery. Postoperative tumour specimens were made corresponding to the transverse image of MRI. One hundred and two tissue samples were obtained and pathologically divided into tumour survival areas (non-cartilaginous and cartilaginous tumour viable areas) and tumour-nonviable areas (non-cartilaginous tumour necrosis areas, post-necrotic tumour collagen areas, and tumour necrotic cystic/haemorrhagic and secondary aneurismal bone cyst areas). The MRI parameters, including standardised apparent diffusion coefficient (ADC) values, signal intensity values of T2-weighted imaging (T2WI) and subtract-enhanced T1-weighted imaging (ST1WI) were used to train machine learning models based on the random forest algorithm. Three classification tasks of distinguishing tumour survival, non-cartilaginous tumour survival, and cartilaginous tumour survival from tumour nonviable were evaluated by five-fold cross-validation.

RESULTS

For distinguishing non-cartilaginous tumour survival from tumour nonviable, the classifier constructed with ADC achieved an AUC of 0.93, while the classifier with multi-parametric MRI improved to 0.97 (P = 0.0933). For distinguishing tumour survival from tumour nonviable, the classifier with ADC achieved an AUC of 0.83, while the classifier with multi-parametric MRI improved to 0.90 (P < 0.05). For distinguishing cartilaginous tumour survival from tumour nonviable, the classifier with ADC achieved an AUC of 0.61, while the classifier with multi-parametric MRI parameters improved to 0.81(P < 0.05).

CONCLUSIONS

The combination of multi-parametric MRI and machine learning significantly improved the discriminating ability of viable cartilaginous tumour components. Our study suggests that this method may provide an objective and accurate basis for NACT response evaluation in osteosarcoma.

Assessment of carotid atherosclerotic disease using three-dimensional cardiovascular magnetic resonance vessel wall imaging: comparison with digital subtraction angiography

BACKGROUND

A three-dimensional (3D) cardiovascular magnetic resonance (CMR) vessel wall imaging (VWI) technique based on 3D T1 weighted (T1w) Sampling Perfection with Application-optimized Contrast using different flip angle Evolutions (SPACE) has recently been used as a promising CMR imaging modality for evaluating extra-cranial and intra-cranial vessel walls. However, this technique is yet to be validated against the current diagnostic imaging standard. We therefore aimed to evaluate the diagnostic performance of 3D CMR VWI in characterizing carotid disease using intra-arterial digital subtraction angiography (DSA) as a reference.

METHODS

Consecutive patients with at least unilateral > 50% carotid stenosis on ultrasound were scheduled to undergo interventional therapy were invited to participate. The following metrics were measured using 3D CMR VWI and DSA: lumen diameter of the common carotid artery (CCA) and segments C1-C7, stenosis diameter, reference diameter, lesion length, stenosis degree, and ulceration. We assessed the diagnostic sensitivity, specificity, accuracy, and receiver operating characteristic (ROC) curve of 3D CMR VWI, and used Cohen's kappa, the intraclass correlation coefficient (ICC), and Bland-Altman analyses to assess the diagnostic agreement between 3D CMR VWI and DSA.

RESULTS

The ICC (all ICCs ≥0.96) and Bland-Altman plots indicated excellent inter-reader agreement in all individual morphologic measurements by 3D CMR VWI. Excellent agreement in all individual morphologic measurements were also found between 3D CMR VWI and DSA. In addition, 3D CMR VWI had high sensitivity (98.4, 97.4, 80.0, 100.0%), specificity (100.0, 94.5, 99.1, 98.0%), and Cohen's kappa (0.99, 0.89, 0.84, 0.96) for detecting stenosis > 50%, stenosis > 70%, ulceration, and total occlusion, respectively, using DSA as the standard. The AUC of 3D CMR VWI for predicting stenosis > 50 and > 70% were 0.998 and 0.999, respectively.

CONCLUSIONS

The 3D CMR VWI technique enables accurate diagnosis and luminal feature assessment of carotid artery atherosclerosis, suggesting that this imaging modality may be useful for routine imaging workups and provide comprehensive information for both the vessel wall and lumen.

Radiomics performs comparable to morphologic assessment by expert radiologists for prediction of response to neoadjuvant chemoradiotherapy on baseline staging MRI in rectal cancer

PURPOSE

To compare the performance of advanced radiomics analysis to morphological assessment by expert radiologists to predict a good or complete response to chemoradiotherapy in rectal cancer using baseline staging MRI.

MATERIALS AND METHODS

We retrospectively assessed the primary staging MRIs [prior to chemoradiotherapy (CRT)] of 133 rectal cancer patients from 2 centers. First, two expert radiologists subjectively estimated the likelihood of achieving a "complete response" (ypT0) and "good response" (TRG 1-2), using a 5-point score (based on TN-stage, MRF/EMVI-status, size/signal/shape). Next, tumor volumes were segmented on high b value DWI (semi-automated, corrected by 2 non-expert and 2-expert readers, resulting in 5 segmentations), copied to the remaining sequences after which a total of 2505 radiomic features were extracted from T2W, low and high b value DWI and ADC. Stability of features for noise due to inter-reader and inter-scanner and protocol variations was assessed using intraclass correlation (ICC) and the Kruskal-Wallis test. Using data from center 1 (n = 86; training set), top 9 features were selected using minimum Redundancy Maximum Relevance and combined in a logistic regression model. Finally, diagnostic performance of the fitted models was assessed on data from center 2 (n = 47; validation set) and compared to the performance of the radiologists.

RESULTS

The Radiomic models resulted in AUCs of 0.69-0.79 (with similar results for the segmentations performed by expert/non-expert readers) to predict response, results similar to the morphologic prediction by the expert radiologists (AUC 0.67-0.83). Radiomics using semi-automatically generated segmentations (without manual input) did not result in significant predictive performance.

CONCLUSIONS

Radiomics could predict response to therapy with comparable diagnostic performance as expert radiologists, regardless of whether image segmentation was performed by non-expert or expert readers, indicating that expert input is not required in order for the radiomics workflow to produce significant predictive performance.

Multiparametric MRI in rectal cancer

MRI has a pivotal role in both pretreatment staging and posttreatment evaluation of rectal cancer. The accuracy of MRI in pretreatment staging is higher compared with posttreatment evaluation. This occurs due to similar signal intensities of tumoral and posttreatment fibrotic, necrotic, and inflamed tissue. This limitation occurs with conventional MRI of the rectum with morphologic sequences. There is a need towards increasing the accuracy of MRI, especially for posttreatment evaluation. The term multiparametric MRI implies addition of functional sequences, namely, diffusion and perfusion to the routine protocol. This review summarizes the technique, potential implications and previously published studies about multiparametric MRI of rectal cancer.

Diffusion and perfusion MR parameters to assess preoperative short-course radiotherapy response in locally advanced rectal cancer: a comparative explorative study among Standardized Index of Shape by DCE-MRI, intravoxel incoherent motion- and diffusion kurtosis imaging-derived parameters

PURPOSE

To assess preoperative short-course radiotherapy (SCR) tumor response in locally advanced rectal cancer (LARC) by means of Standardized Index of Shape (SIS) by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters derived from diffusion-weighted MRI (DW-MRI).

MATERIALS AND METHODS

Thirty-four patients with LARC who underwent MRI scans before and after SCR followed by delayed surgery, retrospectively, were enrolled. SIS, ADC, IVIM parameters [tissue diffusion (D_t), pseudo-diffusion (D_p), perfusion fraction (f_p)] and DKI parameters [mean diffusivity (MD), mean of diffusional kurtosis (MK)] were calculated for each patient. IVIM parameters were estimated using two methods, namely conventional biexponential fitting (CBFM) and variable projection (VARPRO). After surgery, the pathological TNM and tumor regression grade (TRG) were estimated. For each parameter, percentage changes between before and after SCR were evaluated. Furthermore, an artificial neural network was trained for outcome prediction. Nonparametric sample tests and receiver operating characteristic curve (ROC) analysis were performed.

RESULTS

Fifteen patients were classified as responders (TRG ≤ 2) and 19 as not responders (TRG > 3). Seven patients had TRG 1 (pathological complete response, pCR). Mean and standard deviation values of pre-treatment CBFM D_p and mean value of VARPRO D_p pre-treatment showed statistically significant differences to predict pCR. (p value at Mann-Whitney test was 0.05, 0.03 and 0.008, respectively.) Exclusively SIS percentage change showed significant differences between responder and non-responder patients after SCR (p value << 0.001) and to assess pCR after SCR (p value << 0.001). The best results to predict pCR were obtained by VARPRO Fp mean value pre-treatment with area under ROC of 0.84, a sensitivity of 96.4%, a specificity of 71.4%, a positive predictive value (PPV) of 92.9%, a negative predictive value (NPV) of 83.3% and an accuracy of 91.2%. The best results to assess after treatment complete pathological response were obtained by SIS with an area under ROC of 0.89, a sensitivity of 85.7%, a specificity of 92.6%, a PPV of 75.0%, a NPV of 96.1% and an accuracy of 91.2%. Moreover, the best results to differentiate after treatment responders vs. non-responders were obtained by SIS with an area under ROC of 0.94, a sensitivity of 93.3%, a specificity of 84.2%, a PPV of 82.4%, a NPV of 94.1% and an accuracy of 88.2%. Promising initial results were obtained using a decision tree tested with all ADC, IVIM and DKI extracted parameter: we reached high accuracy to assess pathological complete response after SCR in LARC (an accuracy of 85.3% to assess pathological complete response after SCR using VARPRO D_p mean value post-treatment, ADC standard deviation value pre-treatment, MD standard deviation value post-treatment).

CONCLUSION

SIS is a hopeful DCE-MRI angiogenic biomarker to assess preoperative treatment response after SCR with delayed surgery. Furthermore, an important prognostic role was obtained by VARPRO F_p mean value pre-treatment and by a decision tree composed by diffusion parameters derived by DWI and DKI to assess pathological complete response.

Locally advanced rectal cancer: qualitative and quantitative evaluation of diffusion-weighted magnetic resonance imaging in restaging after neoadjuvant chemo-radiotherapy

PURPOSE

To determine the added value of qualitative and quantitative evaluation of diffusion-weighted magnetic resonance imaging (DWI) in locally advanced rectal cancer (LARC) restaging after neoadjuvant chemo-radiotherapy (CRT).

MATERIALS AND METHODS

A retrospective study was performed of 21 patients with LARC treated with CRT. All patients were evaluated with 1.5 T conventional magnetic resonance imaging (MRI) and DWI (0-1000 s/mm²) before starting therapy and after neoadjuvant CRT. All included patients underwent surgery after CRT: the histopathological evaluation of surgical specimens represented the reference standard for local staging after neoadjuvant therapy. The qualitative analysis was carried out by two operators in consensus, who reviewed the conventional MR image set [T1-weighted and T2-weighted morphological sequences + dynamic contrast-enhanced sequences (DCE)] and the combined set of conventional and DW images. For the quantitative analysis, the apparent diffusion coefficient (ADC) values were measured at each examination. For each lesion, the mean ADC value (ADCpre and ADCpost) and the ΔADC (ADCpost - ADCpre) were calculated, and values of the three groups of response [complete response (pCR), partial response (pPR), stable disease (pSD)] were compared.

RESULTS

In LARC restaging, conventional MRI showed a sensitivity of 80% and a specificity of 50%, with a total diagnostic capacity of 71.40%, while by adding DWI sensitivity increased to 100%, specificity to 67%, and total diagnostic capacity to 90.40%. ΔADC correlates with treatment response and a cutoff of 1.35 × 10^-3 mm²/s predicts the pCR with a sensitivity of 93.3% and a specificity of 83.3%.

CONCLUSIONS

Adding DWI to conventional sequences may improve MRI capability to evaluate tumor response to CRT. The quantitative DWI assessment is promising, but larger studies are required.

Primary and post-chemoradiotherapy staging using MRI in rectal cancer: the role of diffusion imaging in the assessment of perirectal infiltration

PURPOSE

To analyze changes in MRI diagnostic accuracy in main rectal tumor (T) evaluation resulting from the use of diffusion-weighted imaging (DWI), according to the degree of experience of the radiologist.

METHODS

This is a cross-sectional study of a database including one hundred 1.5 T MRI records (2011-2016) from patients with biopsy-proven rectal cancer, including primary staging and post-chemoradiotherapy follow-up. All cases were individually blindedly reviewed by ten radiologists: three experienced in rectal cancer, three specialized in other areas, and four residents. Each case was assessed twice to detect perirectal infiltration: first, evaluating just high-resolution T2-weighted sequences (HRT2w); second, evaluation of DWI plus HRT2w sequences. Results were pooled by experience, calculating accuracy (area under ROC curve), sensitivity and specificity, predictive values, likelihood ratios, and overstaging/understaging. Histology of surgical specimens provided the reference standard.

RESULTS

DWI significantly improved specificity by experienced radiologists in primary staging (63.2% to 75.9%) and, to a lesser extent, positive likelihood ratio (2.06 to 2.87); minimal changes were observed post-chemoradiotherapy, with a slight decrease of accuracy (0.657 to 0.626). Inexperienced radiologists showed a similar pattern, but with slight enhancement post-chemoradiotherapy (accuracy 0.604 to 0.621). Residents experienced small changes, with increased sensitivity/decreased specificity in both primary (69% to 72%/67.2% to 64.7%) and post-chemoradiotherapy (68.1% to 73.6%/47.3% to 44.6%) staging.

CONCLUSIONS

Adding DWI to HRT2w significantly improved specificity for the detection of perirectal infiltration at primary staging by experienced radiologists and also by inexperienced ones, although to a lesser extent. In the post-neoadjuvant treatment subgroup, only minimal changes were observed.

Sensitivity of Various Evaluating Modalities for Predicting a Pathologic Complete Response After Preoperative Chemoradiation Therapy for Locally Advanced Rectal Cancer

PURPOSE

We investigated the sensitivity of various evaluating modalities in predicting a pathologic complete response (pCR) after preoperative chemoradiation therapy (PCRT) for locally advanced rectal cancer (LARC).

METHODS

From a population of 2,247 LARC patients who underwent PCRT followed by surgery at Asan Medical Center, Seoul, Korea from January 2007 to June 2016, we retrospectively analyzed 313 patients (14.1%) who showed a pCR after surgery. Transrectal ultrasound (TRUS), high-resolution magnetic resonance imaging (MRI), abdominopelvic computed tomography (AP-CT), and endoscopy were performed within 2 weeks prior to surgery.

RESULTS

Of the 313 patients analyzed, 256 (81.8%) had a pCR after radical surgery and 57 (18.2%) showed total regression after local excision. Preoperative TRUS, MRI, and AP-CT were performed in 283, 305, and 139 patients, respectively. Among these 3 groups, a prediction of a pCR of the primary tumor was made in 41 (14.5%), 51 (16.7%), and 27 patients (19.4%), respectively, before surgery. A prediction of a clinical N0 stage was made in 204 patients (88.3%) using TRUS, 130 (52.2%) using MRI, and 78 (65.5%) using AP-CT. Of the 211 patients who underwent endoscopy, 87 (41.2%) had a mention of clinical CR in their records. A prediction of a pathologic CR was made for 124 patients (39.6%) through at least one diagnostic modality.

CONCLUSION

The various evaluation methods for predicting a pCR after PCRT show a predictive sensitivity of 0.15-0.41 for primary tumors and 0.52-0.88 for lymph nodes. Endoscopy is a relatively superior modality for predicting the pCR of the primary tumor of LARC patients.

Radiomics features on radiotherapy treatment planning CT can predict patient survival in locally advanced rectal cancer patients

This retrospective study was to investigate whether radiomics feature come from radiotherapy treatment planning CT can predict prognosis in locally advanced rectal cancer patients treated with neoadjuvant chemoradiation followed by surgery. Four-hundred-eleven locally advanced rectal cancer patients which were treated with neoadjuvant chemoradiation enrolled in this study. All patients’ radiotherapy treatment planning CTs were collected. Tumor was delineated on these CTs by physicians. An in-house radiomics software was used to calculate 271 radiomics features. The results of test-retest and contour-recontour studies were used to filter stable radiomics (Spearman correlation coefficient > 0.7). Twenty-one radiomics features were final enrolled. The performance of prediction model with the radiomics or clinical features were calculated. The clinical outcomes include local control, distant control, disease-free survival (DFS) and overall survival (OS). Model performance C-index was evaluated by C-index. Patients are divided into two groups by cluster results. The results of chi-square test revealed that the radiomics feature cluster is independent of clinical features. Patients have significant differences in OS (p = 0.032, log rank test) for these two groups. By supervised modeling, radiomics features can improve the prediction power of OS from 0.672 [0.617 0.728] with clinical features only to 0.730 [0.658 0.801]. In conclusion, the radiomics features from radiotherapy CT can potentially predict OS for locally advanced rectal cancer patients with neoadjuvant chemoradiation treatment.

Optimized Parameters of Diffusion-Weighted MRI for Prediction of the Response to Neoadjuvant Chemoradiotherapy for Locally Advanced Rectal Cancer

Aim

To identify the optimal diffusion-weighted MRI-derived parameters for predicting the response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

Methods

This prospective study enrolled 92 patients who underwent neoadjuvant chemoradiotherapy. Diffusion-weighted MRI sequences with two b-value combinations of b (0, 800) and b (0, 1000) were acquired before the start of neoadjuvant chemoradiotherapy and surgery. The pathological tumor regression grade was obtained according to the Mandard criteria, recommended by the seventh edition of the American Joint Committee on Cancer, to act as the reference standard. Pathological good responders (pathological tumor regression grade 1-2) were compared with poor responders (pathological tumor regression grade 3–5).

Results

The good responder group contained 37 (40.2%) patients and the poor responder group 55 (59.8%) patients. Both before and after neoadjuvant chemoradiotherapy, the mean ADC value for b = 1000 was significantly higher than that for b = 800. In the two patient groups, the post-ADC value and ΔADC for b = 800 were significantly lower than those for b = 1000, but percentages of ADC increase for b = 800 and b = 1000 showed no significant difference.

Conclusions

The percentage of ADC increase, as an optimized predictor unaffected by different b-values, may have a significant role in differentiating those patients with a good response to N-CRT from those with a poor response.