Neoadjuvant chemotherapy evaluation by MRI volumetry in rectal cancer followed by chemoradiation and total mesorectal excision: Initial experience

MRI Tumor Regression Grade Combined with T2-Weighted Volumetry May Predict Histopathological Response in Locally Advanced Rectal Cancer following Neoadjuvant Chemoradiotherapy-A New Scoring System Proposal

Modern studies focus on the discovery of innovative methods to improve the value of post-treatment magnetic resonance imaging (MRI) in the prediction of pathological responses to preoperative neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). The aim of this study was to assess the potential benefits of combining magnetic resonance tumor regression grade (mrTRG) with T2-weighted volumetry in the prediction of pathological responses to nCRT in LARC. This was a cohort study conducted on patients with histopathologically confirmed LARC in a period from 2020 to 2022. After histopathological verification, all patients underwent initial MRI studies, while the follow-up MRI was performed after nCRT. Tumor characteristics, MRI estimated tumor regression grade (mrTRG) and tumor volumetry were evaluated both initially and at follow-up. All patients were classified into responders and non-responders according to pathological tumor regression grade (pTRG) and mrTRG. A total of 71 patients, mostly male (66.2%) were included in the study. The median tumor volume reduction rate was significantly higher in nCRT-responders compared to non-responders (79.9% vs. 63.3%) (p = 0.003). Based on ROC analysis, optimal cut-off value for tumor volume reduction rate was determined with an area under the curve (AUC) value of 0.724 (p = 0.003). Using the tumor volume reduction rate ≥75% with the addition of response to nCRT according to mrTRG, a new scoring system for prediction of pTRG to preoperative nCRT in LARC was developed. Diagnostic performance of prediction score was tested and the sensitivity, PPV, specificity, and NPV were 81.8%, 56.3%, 71.4%, and 89.7%, respectively. The combination of mrTRG and T2-weighted volumetry increases the MRI-based prediction of pTRG to preoperative nCRT in LARC. The proposed scoring system could aid in distinguishing responders to nCRT, as these patients could benefit from organ-preserving treatment and a "watch and wait" strategy.

MRI restaging of rectal cancer: The RAC (Response-Anal canal-CRM) analysis joint consensus guidelines of the GRERCAR and GRECCAR groups

PURPOSE

To develop guidelines by international experts to standardize data acquisition, image interpretation, and reporting in rectal cancer restaging with magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Evidence-based data and experts' opinions were combined using the RAND-UCLA Appropriateness Method to attain consensus guidelines. Experts provided recommendations for reporting template and protocol for data acquisition were collected; responses were analysed and classified as "RECOMMENDED" versus "NOT RECOMMENDED" (if ≥ 80% consensus among experts) or uncertain (if < 80% consensus among experts).

RESULTS

Consensus regarding patient preparation, MRI sequences, staging and reporting was attained using the RAND-UCLA Appropriateness Method. A consensus was reached for each reporting template item among the experts. Tailored MRI protocol and standardized report were proposed.

CONCLUSION

These consensus recommendations should be used as a guide for rectal cancer restaging with MRI.

The predictive value of tumor volume reduction ratio on three-dimensional endorectal ultrasound for tumor response to chemoradiotherapy for locally advanced rectal cancer

Background

Preoperative chemoradiotherapy remains part of the standard treatment for patients with locally advanced rectal cancer. Subsequent treatment individualization requires accurate prediction of tumor response to chemoradiotherapy. Three-dimensional endorectal ultrasound (3D-ERUS) can automatically capture and store the images of the rectal wall and rectal cancer with high resolution. In this study, we aimed to assess the correlation and predictive value between tumor volume changes measured on 3D-ERUS and the histopathological tumor response after chemoradiotherapy for patients with locally advanced rectal cancer.

Methods

A total of 54 patients with locally advanced rectal cancer who underwent chemoradiotherapy and had complete 3D-ERUS data pre-and post-chemoradiotherapy were enrolled in the study. The tumor volume pre-and post-chemoradiotherapy was measured manually on 3D-ERUS, and the tumor volume reduction ratio was calculated. The histopathological tumor regression grade (TRG) was used to assess tumor response. The differences in volumetry parameters were compared between groups with varying tumor response. The diagnostic efficacy of the tumor volume reduction ratio was evaluated by the receiver operating characteristic (ROC) curve.

Results

The mean age of all patients was 55.19±12.46 years. The relative proportions of TRG 0–3 were 29.6% (16/54), 16.6% (9/54), 50% (27/54), and 3.8% (2/54), respectively. The median tumor volumes post-chemoradiotherapy in good responders (TRG 0–1, median tumor volume =3.26 cm³) and the complete response group (TRG 0, median tumor volume =2.61 cm³) were smaller than those in poor responders (TRG 2–3, median tumor volume =5.43 cm³) and the partial response group (TRG 1–3, median tumor volume =4.00 cm³), while tumor volume reduction ratios were higher than those of poor responders (79.32% vs. 59.67%) and the partial response group (82.22% vs. 61.64%), with significant differences (all P values <0.05). The ROC curves showed that the cut-off values of the tumor volume reduction ratio to predict good responders and complete response were 67.77% and 72.02%, respectively. The corresponding areas under the curve in the prediction of good responders and complete response were 0.830 and 0.829, respectively.

Conclusions

The tumor volume reduction ratio measured on 3D-ERUS might be a helpful indicator for tumor response in patients with locally advanced rectal cancer.

Treatment response prediction using MRI-based pre-, post-, and delta-radiomic features and machine learning algorithms in colorectal cancer

OBJECTIVES

We evaluate the feasibility of treatment response prediction using MRI-based pre-, post-, and delta-radiomic features for locally advanced rectal cancer (LARC) patients treated by neoadjuvant chemoradiation therapy (nCRT).

MATERIALS AND METHODS

This retrospective study included 53 LARC patients divided into a training set (Center#1, n = 36) and external validation set (Center#2, n = 17). T2-weighted (T2W) MRI was acquired for all patients, 2 weeks before and 4 weeks after nCRT. Ninety-six radiomic features, including intensity, morphological and second- and high-order texture features were extracted from segmented 3D volumes from T2W MRI. All features were harmonized using ComBat algorithm. Max-Relevance-Min-Redundancy (MRMR) algorithm was used as feature selector and k-nearest neighbors (KNN), Naïve Bayes (NB), Random forests (RF), and eXtreme Gradient Boosting (XGB) algorithms were used as classifiers. The evaluation was performed using the area under the receiver operator characteristic (ROC) curve (AUC), sensitivity, specificity and accuracy.

RESULTS

In univariate analysis, the highest AUC in pre-, post-, and delta-radiomic features were 0.78, 0.70, and 0.71, for GLCM_IMC1, shape (surface area and volume) and GLSZM_GLNU features, respectively. In multivariate analysis, RF and KNN achieved the highest AUC (0.85 ± 0.04 and 0.81 ± 0.14, respectively) among pre- and post-treatment features. The highest AUC was achieved for the delta-radiomic-based RF model (0.96 ± 0.01) followed by NB (0.96 ± 0.04). Overall. Delta-radiomics model, outperformed both pre- and post-treatment features (P-value <0.05).

CONCLUSION

Multivariate analysis of delta-radiomic T2W MRI features using machine learning algorithms could potentially be used for response prediction in LARC patients undergoing nCRT. We also observed that multivariate analysis of delta-radiomic features using RF classifiers can be used as powerful biomarkers for response prediction in LARC.

Prediction of Response to Neoadjuvant Chemoradiotherapy by MRI-Based Machine Learning Texture Analysis in Rectal Cancer Patients

INTRODUCTION

Neoadjuvant chemoradiotherapy (nCRT) followed by surgical resection is the standard treatment for locally advanced rectal cancer (LARC). Radiomics can be used as noninvasive biomarker for prediction of response to therapy. The main aim of this study was to evaluate the association of MRI texture features of LARC with nCRT response and the effect of Laplacian of Gaussian (LoG) filter and feature selection algorithm in prediction process improvement.

METHODS

All patients underwent MRI with a 3T clinical scanner, 1 week before nCRT. For each patient, intensity, shape, and texture-based features were derived from MRI images with LoG filter using the IBEX software and without preprocessing. We identified responder from a non-responder group using 9 machine learning classifiers. Then, the effect of preprocessing LoG filters with 0.5, 1 and 1.5 value on these classification algorithms' performance was investigated. Eventually, classification algorithm's results were compared in different feature selection methods.

RESULT

Sixty-seven patients with LARC were included in the study. Patients' nCRT responses included 11 patients with Grade 0, 19 with Grade 1, 26 with Grade 2, and 11 with Grade 3 according to AJCC/CAP pathologic grading. In MR Images which were not preprocessed, the best performance was for Ada boost classifier (AUC = 74.8) with T2W MR Images. In T1W MR Images, the best performance was for aba boost classifier (AUC = 78.1) with a σ = 1 preprocessing LoG filter. In T2W MR Images, the best performance was for naive Bayesian network classifier (AUC = 85.1) with a σ = 0.5 preprocessing LoG filter. Also, performance of machine learning models with CfsSubsetEval (CF SUB E) feature selection algorithm was better than others.

CONCLUSION

Machine learning can be used as a response predictor model in LARC patients, but its performance should be improved. A preprocessing LoG filter can improve the machine learning methods performance and at the end, the effect of feature selection algorithm on model's performance is clear.

Early MRI predictors of disease-free survival in locally advanced rectal cancer from the GRECCAR 4 trial

BACKGROUND

Tailored neoadjuvant treatment of locally advanced rectal cancer (LARC) may improve outcomes. The aim of this study was to determine early MRI prognostic parameters with which to stratify neoadjuvant treatment in patients with LARC.

METHODS

All patients from a prospective, phase II, multicentre randomized study (GRECCAR4; NCT01333709) were included, and underwent rectal MRI before treatment, 4 weeks after induction chemotherapy and after completion of chemoradiotherapy (CRT). Tumour volumetry, MRI tumour regression grade (mrTRG), T and N categories, circumferential resection margin (CRM) status and extramural vascular invasion identified by MRI (mrEMVI) were evaluated.

RESULTS

A total of 133 randomized patients were analysed. Median follow-up was 41·4 (95 per cent c.i. 36·6 to 45·2) months. Thirty-one patients (23·3 per cent) developed tumour recurrence. In univariable analysis, mrEMVI at baseline was the only prognostic factor associated with poorer outcome (P = 0·015). After induction chemotherapy, a larger tumour volume on MRI (P = 0·019), tumour volume regression of 60 per cent or less (P = 0·002), involvement of the CRM (P = 0·037), mrEMVI (P = 0·026) and a poor mrTRG (P = 0·023) were associated with poor outcome. After completion of CRT, the absence of complete response on MRI (P = 0·004), mrEMVI (P = 0·038) and a poor mrTRG (P = 0·005) were associated with shorter disease-free survival. A final multivariable model including all significant variables (baseline, after induction, after CRT) revealed that Eastern Cooperative Oncology Group performance status (P = 0·011), sphincter involvement (P = 0·009), mrEMVI at baseline (P = 0·002) and early tumour volume regression of 60 per cent or less after induction (P = 0·007) were associated with relapse.

CONCLUSION

Baseline and early post-treatment MRI parameters are associated with prognosis in LARC. Future preoperative treatment should stratify treatment according to baseline mrEMVI status and early tumour volume regression.

Neo-adjuvant chemoradiotherapy response prediction using MRI based ensemble learning method in rectal cancer patients

OBJECTIVES

The aim of this study was to investigate and validate the performance of individual and ensemble machine learning models (EMLMs) based on magnetic resonance imaging (MRI) to predict neo-adjuvant chemoradiation therapy (nCRT) response in rectal cancer patients. We also aimed to study the effect of Laplacian of Gaussian (LOG) filter on EMLMs predictive performance.

METHODS

98 rectal cancer patients were divided into a training (n = 53) and a validation set (n = 45). All patients underwent MRI a week before nCRT. Several features from intensity, shape and texture feature sets were extracted from MR images. SVM, Bayesian network, neural network and KNN classifiers were used individually and together for response prediction. Predictive performance was evaluated using the area under the receiver operator characteristic (ROC) curve (AUC).

RESULTS

Patients' nCRT responses included 17 patients with Grade 0, 28 with Grade 1, 34 with Grade 2, and 19 with Grade 3 according to AJCC/CAP pathologic grading. In without preprocessing MR Image the best result was for Bayesian network classifier with AUC and accuracy of 75.2% and 80.9% respectively, which was confirmed in the validation set with an AUC and accuracy of 74% and 79% respectively. In EMLMs the best result was for 4 (SVM.NN.BN.KNN) classifier EMLM with AUC and accuracy of 97.8% and 92.8% in testing and 95% and 90% in validation set respectively.

CONCLUSIONS

In conclusion, we observed that machine learning methods can used to predict nCRT response in patients with rectal cancer. Preprocessing LOG filters and EL models can improve the prediction process.

Pelvic MRI after induction chemotherapy and before long-course chemoradiation therapy for rectal cancer: What are the imaging findings?

OBJECTIVES

To determine the appearance of rectal cancer on MRI after oxaliplatin-based chemotherapy (ICT) and make a preliminary assessment of MRI's value in predicting response to total neoadjuvant treatment (TNT).

METHODS

In this IRB-approved, HIPAA-compliant, retrospective study between 1 January 2010-20 October 2014, pre- and post-ICT tumour T2 volume, relative T2 signal intensity (rT2SI), node size, signal intensity and border characteristics were assessed in 63 patients (65 tumours) by three readers. The strength of association between the reference standard of histopathological percent tumour response and tumour volume change, rT2SI and lymph node characteristics was assessed with Spearman's correlation coefficient and Wilcoxon's rank sum test. Cox regression was used to assess association between DFS and radiological measures.

RESULTS

Change in T2 volume was not associated with TNT response. Change in rT2SI showed correlation with TNT response for one reader only using selective regions of interest (ROIs) and borderline correlation with response using total volume ROI. There was a significant negative correlation between baseline and post-ICT node size and TNT response (r = -0.25, p = 0.05; r = -0.35, p = 0.005, readers 1 and 2, respectively). Both baseline and post-induction median node sizes were significantly smaller in complete responders (p = 0.03, 0.001; readers 1 and 2, respectively). Change in largest baseline node size and decrease in post-ICT node signal heterogeneity were associated with 100% tumour response (p = 0.04). Nodal sizes at baseline and post-ICT MRI correlated with DFS.

CONCLUSION

In patients undergoing post-ICT MRI, tumour volume did not correlate with TNT response, but decreased lymph node sizes were significantly associated with complete response to TNT as well as DFS. Relative T2SI showed borderline correlation with TNT response.

KEY POINTS

• MRI-based tumour volume after induction chemotherapy and before chemoradiotherapy did not correlate with overall tumour response at the end of all treatment. • Lymph node size after induction chemotherapy and before chemoradiotherapy was strongly associated with complete pathological response after all treatment. • Lymph node sizes at baseline and post-induction chemotherapy MRI correlated with disease-free survival.

Quantitative Perfusion Analysis of the Rectum Using Golden-Angle Radial Sparse Parallel Magnetic Resonance Imaging: Initial Experience and Comparison to Time-Resolved Angiography With Interleaved Stochastic Trajectories

OBJECTIVES

Purpose of this study was to compare the quality of perfusion maps obtained from prototypical free-breathing magnetic resonance imaging (MRI) with continuous golden-angle radial sampling and iterative reconstruction (GRASP) to conventional acquisition using time-resolved angiography with interleaved stochastic trajectories (TWIST) in patients with rectal cancer.

MATERIAL AND METHODS

Forty cases were included for retrospective analysis. Twenty of the patients received routine multiparametric MRI at 3 T for rectal cancer staging, including perfusion measurement with GRASP or TWIST (10 patients for each technique, including 5 prechemoradiation and 5 postchemoradiation). Twenty patients without history of rectal disease served as control group (10 GRASP, 10 TWIST). GRASP images were reconstructed at temporal resolution of 3.45 seconds (21 spokes/frame). A voxel-by-voxel deconvolution approach was used to determine rectal plasma flow (mL/100 mL per minute). Regions of interest were placed at 3 levels within the tumor and normal rectum (lower, middle, and upper part). The quality of morphologic images, perfusion maps, and arterial input function were scored by 2 blinded radiologists. Independent t tests were applied.

RESULTS

Three patients of the TWIST control group had to be excluded due to technical failure of the sequence. Significantly higher scores for the perfusion maps and arterial input functions (total cohort) were obtained using GRASP (P < 0.05). Artifacts in the perfusion maps were rated significantly lower than for TWIST (P < 0.05). In the healthy rectum cohort, the average plasma flow of normal rectal wall was 31.78 ± 7.39 mL/100 mL per minute with GRASP, compared with 77.62 ± 34.08 mL/100 mL per minute with TWIST, indicating much lower variance for GRASP. Plasma flow values obtained with both methods enabled distinguishing between normal rectal wall and rectal cancer, both before and after chemoradiation. Morphologic image quality was generally higher with GRASP (P < 0.01).

CONCLUSIONS

GRASP perfusion imaging can distinguish between normal rectum and rectal cancers with higher image quality and less variance than TWIST. Additional morphologic assessment with high spatial resolution from the GRASP acquisition may increase the accuracy and diagnostic confidence of the examination.

The Pretreatment Systemic Inflammatory Response is an Important Determinant of Poor Pathologic Response for Patients Undergoing Neoadjuvant Therapy for Rectal Cancer

Background

Not all patients respond equally to neoadjuvant chemoradiotherapy (nCRT), with subsequent effects on survival. The systemic inflammatory response has been shown to predict long-term outcomes in colorectal cancer. The current study examined the association between systemic inflammation and nCRT in patients with rectal cancer.

Methods

Between 1999 and 2010, patients who underwent nCRT were identified. Serum measurements of hemoglobin, C-reactive protein, albumin, modified Glasgow prognostic score (mGPS), and differential white cell counts were obtained before and after nCRT. The Rödel scoring system measured pathologic tumor regression, and magnetic resonance imaging and computed tomography determined radiologic staging.

Results

The study included 79 patients. Of these patients, 37% were radiologically downstaged, and 44% were categorized as showing a good pathologic response (Rödel scores 3 and 4). As a validated measure of the systemic inflammatory response, mGPS (P = 0.022) was associated with a poor pathologic response to nCRT. A radiologic response was associated with a good pathologic response to treatment (P = 0.003). A binary logistic regression model identified mGPS (odds ratio [OR] 0.27; 95% confidence interval [CI] 0.07–0.96; P = 0.043) and radiologic response (OR 0.43; 95% CI 0.18–0.99; P = 0.048) as strong independent predictors of a pathologic response to treatment.

Conclusion

The current study showed that a systemic inflammatory response before nCRT is associated with a poor pathologic response. Further study in a prospective controlled trial setting is warranted.

Multiparametric MRI in the assessment of response of rectal cancer to neoadjuvant chemoradiotherapy: A comparison of morphological, volumetric and functional MRI parameters

PURPOSE

To compare morphological and functional MRI metrics and determine which ones perform best in assessing response to neoadjuvant chemoradiotherapy (CRT) in rectal cancer.

MATERIALS AND METHODS

This retrospective study included 24 uniformly-treated patients with biopsy-proven rectal adenocarcinoma who underwent MRI, including diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) sequences, before and after completion of CRT. On all MRI exams, two experienced readers independently measured longest and perpendicular tumour diameters, tumour volume, tumour regression grade (TRG) and tumour signal intensity ratio on T2-weighted imaging, as well as tumour volume and apparent diffusion coefficient on DW-MRI and tumour volume and transfer constant K^trans on DCE-MRI. These metrics were correlated with histopathological percent tumour regression in the resected specimen (%TR). Inter-reader agreement was assessed using the concordance correlation coefficient (CCC).

RESULTS

For both readers, post-treatment DW-MRI and DCE-MRI volumetric tumour assessments were significantly associated with %TR; DCE-MRI volumetry showed better inter-reader agreement (CCC=0.700) than DW-MRI volumetry (CCC=0.292). For one reader, mrTRG, post-treatment T2 tumour volumetry and assessments of volume change made with T2, DW-MRI and DCE-MRI were also significantly associated with %TR.

CONCLUSION

Tumour volumetry on post-treatment DCE-MRI and DW-MRI correlated well with %TR, with DCE-MRI volumetry demonstrating better inter-reader agreement.

KEY POINTS

• Volumetry on post-treatment DCE-/DW-MRI sequences correlated well with histopathological tumour regression. • DCE-MRI volumetry demonstrated good inter-reader agreement. • Inter-reader agreement was higher for DCE-MRI volumetry than for DW-MRI volumetry. • DCE-MRI volumetry merits further investigation as a metric for evaluating treatment response.

Combined T2w volumetry, DW-MRI and DCE-MRI for response assessment after neo-adjuvant chemoradiation in locally advanced rectal cancer

BACKGROUND

To assess the value of combined T2-weighted magnetic resonance imaging (MRI) (T2w) volumetry, diffusion-weighted (DW)-MRI and dynamic contrast enhanced (DCE)-MRI for pathological response prediction after neo-adjuvant chemoradiation (CRT) in locally advanced rectal cancer (LARC).

MATERIAL AND METHODS

MRI with DW-MRI and DCE-MRI sequences was performed before start of CRT and before surgery. After surgery, the tumor regression grade (TRG) was obtained based on the score by Mandard et al. Pathological complete responders (pCR, TRG 1), and pathological good responders (GR, TRG 1 + 2) were compared to non-pCR and non-GR patients, respectively.

RESULTS

In total 55 patients were analyzed, six had a pCR (10.9%) and 10 a GR (18.2%). Favorable responders had a larger decrease in tumor volume and Ktrans and a larger increase in apparent diffusion coefficient (ADC) values compared to non-responders. ADC change showed the best diagnostic accuracy for pCR. For GR, the model including ADC change and volume change showed the best diagnostic performance. However, this performance was not statistically better compared to the model with ADC change alone. Inclusion of Ktrans change did not increase the diagnostic accuracy for pathological favorable response.

CONCLUSIONS

This explorative study showed that ADC change is a promising diagnostic tool for pCR and GR. Volume decrease showed potential limited additional diagnostic value for GR while Ktrans change showed no additional diagnostic value for pCR and GR.

Endometrial Cancer: Combined MR Volumetry and Diffusion-weighted Imaging for Assessment of Myometrial and Lymphovascular Invasion and Tumor Grade

PURPOSE

To investigate magnetic resonance (MR) volumetry of endometrial tumors and its association with deep myometrial invasion, tumor grade, and lymphovascular invasion and to assess the value of apparent diffusion coefficient (ADC) histographic analysis of the whole tumor volume for prediction of tumor grade and lymphovascular invasion.

MATERIALS AND METHODS

The institutional review board approved this retrospective study; patient consent was not required. Between May 2010 and May 2012, 70 women (mean age, 64 years; range, 24-91 years) with endometrial cancer underwent preoperative MR imaging, including axial oblique and sagittal T2-weighted, dynamic contrast material-enhanced, and diffusion-weighted imaging. Volumetry of the tumor and uterus was performed during the six sequences, with manual tracing of each section, and the tumor volume ratio (TVR) was calculated. ADC histograms were generated from pixel ADCs from the whole tumor volume. The threshold of TVR associated with myometrial invasion was assessed by using receiver operating characteristic curves. An independent sample Mann Whitney U test was used to compare differences in ADCs, skewness, and kurtosis between tumor grade and the presence of lymphovascular invasion.

RESULTS

No significant difference in tumor volume and TVR was found among the six MR imaging sequences (P = .95 and .86, respectively). A TVR greater than or equal to 25% allowed prediction of deep myometrial invasion with sensitivity of 100% and specificity of 93% (area under the curve, 0.96; 95% confidence interval: 0.86, 0.99) at axial oblique diffusion-weighted imaging. A TVR of greater than or equal to 25% was associated with grade 3 tumors (P = .0007) and with lymphovascular invasion (P < .0001). There was no significant difference in the ADCs between grades 1 and 2 tumors (P > .05). The minimum, 10th, 25th, 50th, 75th, and 90th percentile ADCs were significantly lower in grade 3 tumors than in grades 1 and 2 tumors (P < .02).

CONCLUSION

The combination of whole tumor volume and ADC can be used for prediction of tumor grade, lymphovascular invasion, and depth of myometrial invasion.

MRI volumetry for prediction of tumour response to neoadjuvant chemotherapy followed by chemoradiotherapy in locally advanced rectal cancer

OBJECTIVE

To investigate if MRI-assessed tumour volumetry correlates with histological tumour response to neoadjuvant chemotherapy (NACT) and subsequent chemoradiotherapy (CRT) in locally advanced rectal cancer (LARC).

METHODS

Data from 69 prospectively enrolled patients with LARC receiving NACT followed by CRT and radical surgery were analysed. Whole-tumour volumes were contoured in T2 weighted MR images obtained pre-treatment (VPRE), after NACT (VNACT) and after the full course of NACT followed by CRT (VCRT). VPRE, VNACT and tumour volume changes relative to VPRE, ΔVNACT and ΔVCRT were calculated and correlated to histological tumour regression grade (TRG).

RESULTS

61% of good histological responders (TRG 1-2) to NACT followed by CRT were correctly predicted by combining VPRE < 10.5 cm(3), ΔVNACT > -78.2% and VNACT < 3.3 cm(3). The highest accuracy was found for VNACT, with 55.1% sensitivity given 100% specificity. The volume regression after completed NACT and CRT (VCRT) was not significantly different between good and poor responders (TRG 1-2 vs TRG 3-5).

CONCLUSION

MRI-assessed small tumour volumes after NACT correlated with good histological tumour response (TRG 1-2) to the completed course of NACT and CRT. Furthermore, by combining tumour volume measurements before, during and after NACT, more good responders were identified.

ADVANCES IN KNOWLEDGE

MRI volumetry may be a tool for early identification of good and poor responders to NACT followed by CRT and surgery in LARC in order to aid more individualized, multimodal treatment.

Dynamic contrast enhanced MR imaging for rectal cancer response assessment after neo-adjuvant chemoradiation

BACKGROUND

Patient selection for organ sparing treatment after good response to neo-adjuvant chemoradiation (CRT) for locally advanced rectal cancer is challenging as no optimal restaging modality is available after CRT. In this study, we assessed the value of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) for rectal cancer pathological response prediction.

METHODS

In 51 patients with locally advanced rectal cancer, the tumor volume and volume transfer constant (Ktrans) were obtained at 3 Tesla before CRT and surgery. The predictive potential for pathological complete response (pCR) and good response (GR) was assessed. GR was defined as pCR and near-pCR based on the tumor regression grade.

RESULTS

The GR group consisted of 10 patients (19.6%) with six pCR (11.8%). Both the post-CRT tumor volume and post-CRT Ktrans values and the relative change in volume (ΔVolume) and Ktrans (ΔKtrans) were predictive for pathological response. ΔKtrans showed the best predictive potential with a positive predictive value (PPV) of 100% for GR using a cutoff value of 32% reduction in Ktrans. For pCR the best PPV was 80% with a multiparameter model containing ΔVolume and ΔKtrans.

CONCLUSION

DCE-MRI has predictive potential for pathological response after CRT in rectal cancer with the relative ΔKtrans being the most predictive parameter.

MRI and FDG-PET for assessment of response to neoadjuvant chemotherapy in locally advanced rectal cancer

BACKGROUND

The purpose of this study was to assess the value of magnetic resonance imaging (MRI) and additional (18)F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) for tumor response to neoadjuvant chemotherapy (NAC) in patients with locally advanced rectal cancer (LARC).

METHODS

Data on 40 patients with LARC, who were treated with NAC and underwent MRI and FDG-PET/CT before and after NAC, were analyzed retrospectively. Surgery was performed at a median of 6 weeks after NAC and the images were compared with the histological findings. The tumor regression grade 3/4 was classified as a responder.

RESULTS

Sixteen patients were pathological responders. Receiver operating characteristic (ROC) analysis revealed that MRI total volume after NAC (MRI-TV2) and ΔMRI-TV had the highest performance to assess responders (area under the ROC curve [AUC] 0.849 and AUC 0.853, respectively). The reduction rate of the maximum standardized uptake value (ΔSUVmax) was also an informative factor (AUC 0.719). There seems no added value of adding FDG-PET/CT to MRI-TV2 and ΔMRI-TV in assessment of NAC responders judging from changes in AUC (AUC of ΔSUVmax and MRI-TV2 was 0.844, and AUC of ΔSUVmax and ΔMRI-TV was 0.846).

CONCLUSIONS

MRI-TV2 and ΔMRI-TV were the most accurate factors to assess pathological response to NAC. Although ΔSUVmax by itself was also informative, the addition of FDG-PET/CT to MRI did not improve performance. Patients with LARC who were treated by induction chemotherapy should receive an MRI examination before and after NAC to assess treatment response. A more than 70 % volume reduction shown by MRI volumetry may justify the omission of subsequent radiotherapy.

Stage and size using magnetic resonance imaging and endosonography in neoadjuvantly-treated rectal cancer

AIM: To assess the stage and size of rectal tumours using 1.5 Tesla (1.5T) magnetic resonance imaging (MRI) and three-dimensional (3D) endosonography (ERUS).

METHODS: In this study, patients were recruited in a phase I/II trial of neoadjuvant chemotherapy for biopsy-proven rectal cancer planned for surgical resection with or without preoperative radiotherapy. The feasibility and accuracy of 1.5T MRI and 3D ERUS were compared with the histopathology of the fixed surgical specimen (pathology) to determine the stage and size of the rectal cancer before and after neoadjuvant chemotherapy. A Philips Intera 1.5T with a cardiac 5-channel synergy surface coil was used for the MRI, and a B-K Medical Falcon 2101 EXL 3D-Probe was used at 13 MHz for the ERUS. Our hypothesis was that the staging accuracy would be the same when using MRI, ERUS and a combination of MRI and ERUS. For the combination, MRI was chosen for the assessment of the lymph nodes, and ERUS was chosen for the assessment of perirectal tissue penetration. The stage was dichotomised into stage I and stage II or greater. The size was measured as the supero-inferior length and the maximal transaxial area of the tumour.

RESULTS: The staging feasibility was 37 of 37 for the MRI and 29 of 36 for the ERUS, with stenosis as a limiting factor. Complete sets of investigations were available in 18 patients for size and 23 patients for stage. The stage accuracy by MRI, ERUS and the combination of MRI and ERUS was 0.65, 0.70 and 0.74, respectively, before chemotherapy and 0.65, 0.78 and 0.83, respectively, after chemotherapy. The improvement of the post-chemotherapy staging using the combination of MRI and ERUS compared with the staging using MRI alone was significant (P = 0.046). The post-chemotherapy understaging frequency by MRI, ERUS and the combination of MRI and ERUS was 0.18, 0.14 and 0.045, respectively, and these differences were non-significant. The measurements of the supero-inferior length by ERUS compared with MRI were within 1.96 standard deviations of the difference between the methods (18 mm) for tumours smaller than 50 mm. The agreement with pathology was within 1.96 standard deviations of the difference between imaging and pathology for all tumours with MRI (15 mm) and for tumours that did not exceed 50 mm with ERUS (22 mm). Tumours exceeding 50 mm in length could not be reliably measured by ERUS due to the limit in the length of each recording.

CONCLUSION: MRI is preferable to use when assessing the size of large or stenotic rectal tumours. However, staging accuracy is improved by combining MRI with ERUS.