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

Evaluation of treatment response by multiparametric MR imaging in locally advanced rectal tumors following neoadjuvant chemotherapy

PURPOSE

To investigate the effectiveness of multiparametric MRI examination in determining tumor response after neoadjuvant chemoradiotherapy (CRT) in locally advanced rectal tumors.

METHODS

46 patients with locally advanced rectal adenocarcinoma were included and were divided into two groups as complete responders and nonresponders based on Mandard score. On MRI, relative T2w signal intensity and ADC values obtained before and after treatment and tumour volumes in dynamic contrast enhanced images (DCI) were used to determine complete response to treatment.

RESULTS

There were no significant differences between mean ADC values obtained by single slice ADC and three circular ROI methods. There were significant differences between two groups in terms of Post-CRT ADC value, ΔADC and %ΔADC obtained by whole tumour volume ADC method (p < 0.05). There were significant differences between Pre-CRT and Post-CRT volume values. ΔV DCI and %ΔV DCI, ΔV ADC and T2w volume values were significantly lower in complete responders (p < 0.05). In multivariate analysis, sensitivity and specificity were calculated as 88.9% and 91.9% (AUC = 0.943) when Post-CRT mean ADC value and Post-CRT DCI volume values were used together, and sensitivity and specificity were calculated as 88.9% and 94.6% (AUC = 0.949) when ΔADC and Post-CRT DCI volume values were used together.

CONCLUSION

Whole tumour volume mean ADC value is the most useful method to determine treatment response. Post-CRT DCI volume measurement stands out as the most useful method in assessing complete response alone. The highest diagnostic values are achieved when the post-CRT DCI volume is combined with the ADC change value of the whole tumor volume.

The application of the golden-angle radial sparse parallel technique in T restaging of locally advanced rectal cancer after neoadjuvant chemoradiotherapy

PURPOSE

To evaluate the diagnostic performance of Golden-Angle Radial Sparse Parallel (GRASP) MRI in identifying pathological stage T0-1 (ypT0-1) after neoadjuvant chemoradiotherapy (nCRT) in patients with rectal cancer, compared to T2-weighted imaging (T2WI) combined with Diffusion Weighted Imaging (DWI).

METHODS

In this retrospective study, 168 patients were carefully selected based on inclusion criteria that targeted individuals with biopsy-confirmed primary rectal adenocarcinoma, identified via MRI as having locally advanced disease (≥ T3 and/or positive lymph node results) prior to nCRT. Post-nCRT, all MRI images obtained after nCRT were assessed by two observers independently. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy for identifying ypT0-1 based on GRASP and T2 + DWI were calculated. Multivariable regression analysis was used to explore the factors independently associated with ypT0-1 tumor.

RESULTS

45 patients out of these cases were ypT0-1, and the accuracy, sensitivity, specificity, PPV, and NPV of GRASP were higher than the T2 + DWI (88% vs 74%, 93% vs 71%, 86% vs 75%, 71% vs 52% and 97% vs 88%), the AUC in identifying ypT0-1 tumor based on GRASP was 0.90 (95% CI:0.84, 0.94), which was better than the T2 + DWI (0.73; 95% CI: 0.66, 0.80). Multivariable logistic regression analysis showed that the yT stage on GRASP scans was the only factor independently associated with ypT0-1 tumor (P < 0.001).

CONCLUSION

The GRASP helped distinguish ypT0-1 tumor after nCRT and can select patients who may be suitable for local excision.

Response Prediction after Neoadjuvant Chemotherapy for Colon Cancer Using CT Tumor Regression Grade: A Preliminary Study

Purpose

To investigate whether CT-based tumor regression grade (ctTRG) can be used to predict the response to neoadjuvant chemotherapy (NAC) in colon cancer.

Materials and Methods

A total of 53 patients were enrolled. Two radiologists independently assessed the ctTRG using the length, thickness, layer pattern, and luminal and extraluminal appearance of the tumor. Changes in tumor volume were also analyzed using the 3D Slicer software. We evaluated the association between pathologic TRG (pTRG) and ctTRG. Patients with Rödel's TRG of 2, 3, or 4 were classified as responders. In terms of predicting responder and pathologic complete remission (pCR), receiver operating characteristic was compared between ctTRG and tumor volume change.

Results

There was a moderate correlation between ctTRG and pTRG (ρ = -0.540, p < 0.001), and the interobserver agreement was substantial (weighted κ = 0.672). In the prediction of responder, there was no significant difference between ctTRG and volumetry (Az = 0.749, criterion: ctTRG ≤ 3 for ctTRG, Az = 0.794, criterion: ≤ -27.1% for volume, p = 0.53). Moreover, there was no significant difference between the two methods in predicting pCR (p = 0.447).

Conclusion

ctTRG might predict the response to NAC in colon cancer. The diagnostic performance of ctTRG was comparable to that of CT volumetry.

A Comprehensive Prediction Model Based on MRI Radiomics and Clinical Factors to Predict Tumor Response After Neoadjuvant Chemoradiotherapy in Rectal Cancer

RATIONALE AND OBJECTIVES

To establish a prediction model for the efficacy of neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC), using pretreatment magnetic resonance imaging (MRI) multisequence image features and clinical parameters.

MATERIALS AND METHODS

Patients with clinicopathologically confirmed LARC were included (training and validation datasets, n = 100 and 27, respectively). Clinical data of patients were collected retrospectively. We analyzed MRI multisequence imaging features. The tumor regression grading (TRG) system proposed by Mandard et al was adopted. Grade 1-2 of TRG was a good response group, and grade 3-5 of TRG was a poor response group. In this study, a clinical model, a single sequence imaging model, and a comprehensive model combined with clinical imaging were constructed, respectively. The area under the subject operating characteristic curve (AUC) was used to evaluate the predictive efficacy of clinical, imaging, and comprehensive models. The decision curve analysis method evaluated the clinical benefit of several models, and the nomogram of efficacy prediction was constructed.

RESULTS

The AUC value of the comprehensive prediction model is 0.99 in the training data set and 0.94 in the test data set, which is significantly higher than other models. Radiomic Nomo charts were developed using Rad scores obtained from the integrated image omics model, circumferential resection margin(CRM), DoTD, and carcinoembryonic antigen(CEA). Nomo charts showed good resolution. The calibrating and discriminating ability of the synthetic prediction model is better than that of the single clinical model and the single sequence clinical image omics fusion model.

CONCLUSION

Nomograph, based on pretreatment MRI characteristics and clinical risk factors, has the potential to be used as a noninvasive tool to predict outcomes in patients with LARC after nCRT.

Golden-angle radial sparse parallel magnetic resonance imaging of rectal perfusion: utility in the diagnosis of poorly differentiated rectal cancer

Background

The objective of this retrospective investigation is to evaluate the diagnostic efficacy of a dual-parameter strategy that integrates either time-resolved angiography with stochastic trajectories (TWIST) or golden-angle radial sparse parallel (GRASP)-derived dynamic contrast agent-enhanced magnetic resonance imaging (DCE-MRI) with diffusion-weighted imaging (DWI) for the identification of poorly differentiated rectal cancer (RC). The purpose of this investigation is to contrast the aforementioned methodology with conventional single-factor assessments that rely solely on DWI, and ascertain its comparative efficacy.

Methods

This study was not registered on a clinical trial platform. Consecutive individuals diagnosed with non-mucinous rectal adenocarcinoma through endoscopy-guided biopsy between December 2020 and October 2022 were involved in our study. These patients had also undergone DCE-MRI and DWI. The perfusion metrics of influx forward volume transfer constant (Ktrans) and rate constant (Kep), along with the apparent diffusion coefficient (ADC), were quantified by a pair of investigators. The study compared the area under the curve (AUC) of the receiver operating characteristic (ROC) for both sequences to identify poorly differentiated RC. The investigation incorporated patients who fulfilled the specified criteria. The inclusion criteria for the investigation were as follows: (I) a diagnosis of RC proved through pathological examination, either via endoscopically-guided biopsy or surgical resection; (II) availability of complete MRI images; (III) absence of any prior history of neoadjuvant chemoradiotherapy during the MRI scan.

Results

Our investigation comprised a total of 179 participants. Compared to diffusion parameter alone, an integrated assessment of diffusion parameter (ADC) and perfusion parameters (Ktrans or Kep) obtained with GRASP leads to a superior diagnostic accuracy (AUC, 0.97±0.02 vs. 0.89±0.03, 0.97±0.02 vs. 0.89±0.03, P=0.005 and 0.003, respectively); however, there was no additional benefit from ADC with perfusion parameters obtained from TWIST (Ktrans or Kep) (AUC, 0.93±0.04 vs. 0.89±0.03, 0.93±0.03 vs. 0.89±0.03; P= 0.955 and 0.981, respectively, for the integration of ADC with Ktrans and Kep).

Conclusions

By integrating diffusion and perfusion features into a dual-parameter model, the GRASP method enhances the diagnostic efficacy of MRI in discriminating RCs with poor differentiation. Conversely, the TWIST approach did not yield the aforementioned outcome.

Recent Advances in Deep Learning and Medical Imaging for Head and Neck Cancer Treatment: MRI, CT, and PET Scans

Deep learning techniques have been developed for analyzing head and neck cancer imaging. This review covers deep learning applications in cancer imaging, emphasizing tumor detection, segmentation, classification, and response prediction. In particular, advanced deep learning techniques, such as convolutional autoencoders, generative adversarial networks (GANs), and transformer models, as well as the limitations of traditional imaging and the complementary roles of deep learning and traditional techniques in cancer management are discussed. Integration of radiomics, radiogenomics, and deep learning enables predictive models that aid in clinical decision-making. Challenges include standardization, algorithm interpretability, and clinical validation. Key gaps and controversies involve model generalizability across different imaging modalities and tumor types and the role of human expertise in the AI era. This review seeks to encourage advancements in deep learning applications for head and neck cancer management, ultimately enhancing patient care and outcomes.

Predicting lymphovascular invasion in rectal cancer: evaluating the performance of golden-angle radial sparse parallel MRI for rectal perfusion assessment

This study aims to determine whether the dual-parameter approach combined with either time-resolved angiography with stochastic trajectories (TWIST) or golden-angle radial sparse parallel (GRASP) and diffusion-weighted imaging (DWI) has superior diagnostic performance in predicting pathological lymphovascular invasion (pLVI) rectal cancer when compared with traditional single-parameter evaluations using DWI alone. Patients with pathologically confirmed rectal cancer were enrolled. Perfusion (influx forward volume transfer constant [Ktrans] and rate constant [Kep]) and apparent diffusion coefficient (ADC) were measured by two researchers. For both sequences, areas under receiver operating characteristic (ROCs) to predict pLVI-positive rectal cancer were compared. A total of 179 patients were enrolled in our study. A combined analysis of ADC and perfusion parameters (Ktrans) acquired with GRASP yielded a higher diagnostic performance compared with diffusion parameters alone (area under the curve, 0.91 ± 0.03 vs. 0.71 ± 0.06, P < 0.001); However, ADC with GRASP-acquired Kep and ADC with TWIST-acquired perfusion parameters (Ktrans or Kep) did not offer any additional benefit. The Ktrans of the GRASP technique improved the diagnostic performance of multiparametric MRI to predict rectal cancers with pLVI-positive. In contrast, TWIST did not achieve this effect.

Radiomics for the Prediction of Pathological Complete Response to Neoadjuvant Chemoradiation in Locally Advanced Rectal Cancer: A Prospective Observational Trial

(1) Background: An increasing amount of research has supported the role of radiomics for predicting pathological complete response (pCR) to neoadjuvant chemoradiation treatment (nCRT) in order to provide better management of locally advanced rectal cancer (LARC) patients. However, the lack of validation from prospective trials has hindered the clinical adoption of such studies. The purpose of this study is to validate a radiomics model for pCR assessment in a prospective trial to provide informative insight into radiomics validation. (2) Methods: This study involved a retrospective cohort of 147 consecutive patients for the development/validation of a radiomics model, and a prospective cohort of 77 patients from two institutions to test its generalization. The model was constructed using T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI to understand the associations with pCR. The consistency of physicians' evaluations and agreement on pathological complete response prediction were also evaluated, with and without the aid of the radiomics model. (3) Results: The radiomics model outperformed both physicians' visual assessments in the prospective test cohort, with an area under the curve (AUC) of 0.84 (95% confidence interval of 0.70-0.94). With the aid of the radiomics model, a junior physician could achieve comparable performance as a senior oncologist. (4) Conclusion: We have built and validated a radiomics model with pretreatment MRI for pCR prediction of LARC patients undergoing nCRT.

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.

Machine learning-based multiparametric MRI radiomics for predicting poor responders after neoadjuvant chemoradiotherapy in rectal Cancer patients

BACKGROUND

The purpose of this study was to investigate and validate multiparametric magnetic resonance imaging (MRI)-based machine learning classifiers for early identification of poor responders after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).

METHODS

Patients with LARC who underwent nCRT were included in this retrospective study (207 patients). After preprocessing of multiparametric MRI, radiomics features were extracted and four feature selection methods were used to select robust features. The selected features were used to build five machine learning classifiers, and 20 (four feature selection methods × five machine learning classifiers) predictive models for the screening of poor responders were constructed. The predictive models were evaluated according to the area under the curve (AUC), F1 score, accuracy, sensitivity, and specificity.

RESULTS

Eighty percent of all predictive models constructed achieved an AUC of more than 0.70. A predictive model using a support vector machine classifier with the minimum redundancy maximum relevance (mRMR) selection method followed by the least absolute shrinkage and selection operator (LASSO) selection method showed superior prediction performance, with an AUC of 0.923, an F1 score of 88.14%, and accuracy of 91.03%. The predictive performance of the constructed models was not improved by ComBat compensation.

CONCLUSIONS

In rectal cancer patients who underwent neoadjuvant chemoradiotherapy, machine learning classifiers with radiomics features extracted from multiparametric MRI were able to accurately discriminate poor responders from good responders. The techniques should provide additional information to guide patient-tailored treatment.

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

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

Rectal MRI radiomics for predicting pathological complete response: Where we are

Radiomics using rectal MRI radiomics has emerged as a promising approach in predicting pathological complete response. In this study, we present a typical pipeline of a radiomics analysis and review recent studies, exploring applications, development of radiomics methodologies and model construction in pCR prediction. Finally, we will offer our opinion about the future and discuss the next steps of rectal MRI radiomics for predicting pCR.

Dynamic contrast-enhanced magnetic resonance imaging for evaluating early response to radiosurgery in patients with vestibular schwannoma

PURPOSE

This study aimed to use dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to evaluate early treatment response in vestibular schwannoma (VS) patients after radiosurgery.

METHODS

Twenty-four VS patients who underwent gamma knife radiosurgery were prospectively followed up for at least four years. DCE-MRI sequences, in addition to standard MRI protocol, were obtained prior to radiosurgery, at 3 and 6 months. Conventionally, treatment responses based on tumor volume changes were classified as regression or stable (RS), transient tumor enlargement (TTE), and continuous tumor enlargement (CTE). DCE-MRI parameters, such as K^trans, K_ep and V_e, were compared according to follow-up periods and between groups. The diagnostic performance was tested using receiver operating characteristic (ROC) curves.

RESULTS

Changes in tumor volume were as follows at the last 48 months of follow-up: RS in 11 patients (45.8%), TTE in 10 patients (41.7%), and CTE in three patients (12.5%). The median time required to distinguish TTE from CTE using conventional MRI was 12 months (range 9-18). The K^trans and V_e were significantly decreased in patients with RS and TTE at 3 and 6 months, but did not differ significantly in patients with CTE. There were no significant differences in K^trans and V_e between patients with RS and TTE at 3 and 6 months. Both K^trans and V_e demonstrated high diagnostic performance in evaluating early treatment response to radiosurgery in patients with VS.

CONCLUSION

DCE-MRI may aid in the monitoring and early prediction of treatment response in patients with VS following radiosurgery.

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.

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.

Semi-Automatic Volumetric and Standard Three-Dimensional Measurements for Primary Tumor Evaluation and Response to Treatment Assessment in Pediatric Rhabdomyosarcoma

Current prognostic classification of rhabdomyosarcoma in children requires precise measurements of the tumor. The purpose of the study was to compare the standard three-dimensional (3D) measurements with semi-automatic tumor volume measurement method concerning assessment of the primary tumor size and the degree of response to treatment for rhabdomyosarcoma in children. Magnetic Resonance Imaging data on 31 children with treated rhabdomyosarcoma based on the Cooperative Weichteilsarkom Studiengruppe (CWS) guidance was evaluated. Tumor sizes were measured by two methods: 3D standard measurements and semi-automatic tumor volume measurement (VOI) at diagnosis, and after 9 and 17/18 weeks of the induction chemotherapy. Response to treatment and prediction values were assessed. The tumor volume medians calculated using VOI were significantly higher in comparison with those calculated using the 3D method both during the diagnosis as well as after 9 weeks of the chemotherapy and during the 17-18th week of the treatment. The volume measurements based on the generalized estimating equations on the VOI method were significantly better than the 3D method (p = 0.037). The volumetric measurements alone can hardly be considered an unequivocal marker used to make decisions on modification of the therapy in patients with rhabdomyosarcoma.

Tumor size measured by multidetector CT in resectable colon cancer: correlation with regional lymph node metastasis and N stage

Background

Lymph node metastasis (LNM) is a risk factor for poor long-term outcomes and a prognostic factor for disease-free survival in colon cancer. Preoperative lymph node status evaluation remains a challenge. The purpose of this study is to determine whether tumor size measured by multidetector computed tomography (MDCT) could be used to predict LNM and N stage in colon cancer.

Material and methods

One hundred six patients with colon cancer who underwent radical surgery within 1 week of MDCT scan were enrolled. Tumor size including tumor length (Tlen), tumor maximum diameter (Tdia), tumor maximum cross-sectional area (Tare), and tumor volume (Tvol) were measured to be correlated with pathologic LNM and N stage using univariate logistic regression analysis, multivariate logistic analysis, and receiver operating characteristic (ROC) curve analysis.

Results

The inter- and intraobserver reproducibility of Tlen (intraclass correlation coefficient [ICC] = 0.94, 0.95, respectively), Tdia (ICC = 0.81, 0.93, respectively), Tare (ICC = 0.97, 0.91, respectively), and Tvol (ICC = 0.99, 0.99, respectively) parameters measurement are excellent. Univariate logistic regression analysis showed that there were significant differences in Tlen, Tdia, Tare, and Tvol between positive and negative LNM (p < 0.001, 0.001, < 0.001, < 0.001, respectively). Multivariate logistic regression analysis revealed that Tvol was independent risk factor for predicting LNM (odds ratio, 1.082; 95% confidence interval for odds ratio, 1.039, 1.127, p<0.001). Tlen, Tdia, Tare, and Tvol could distinguish N0 from N1 stage (p < 0.001, 0.041, < 0.001, < 0.001, respectively), N0 from N2 (all p < 0.001), N0 from N1-2 (p < 0.001, 0.001, < 0.001, < 0.001, respectively), and N0-1 from N2 (p < 0.001, 0.001, < 0.001, < 0.001, respectively). The area under the ROC curve (AUC) was higher for Tvol than that of Tlen, Tdia, and Tare in identifying LNM (AUC = 0.83, 0.82, 0.69, 0.79), and distinguishing N0 from N1 stage (AUC = 0.79, 0.78, 0.63, 0.74), N0 from N2 stage (AUC = 0.92, 0.89, 0.80, 0.89, respectively), and N0-1 from N2 stage (AUC = 0.84, 0.79, 0.76, 0.83, respectively).

Conclusion

Tumor size was correlated with regional LNM in resectable colon cancer. In particularly, Tvol showed the most potential for noninvasive preoperative prediction of regional LNM and N stage.

Can the mesorectal fat tissue volume be used as a predictive factor in foreseeing the response to neoadjuvant chemoradiotherapy in rectum cancer? A CT-based preliminary study

PURPOSE

This study was to investigate the effect of mesorectal fat tissue volume (MRV) on the pathological response to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer.

METHODS

88 patients who had been diagnosed with locally advanced rectal cancer between January 2017 and June 2020 were reviewed retrospectively. The total abdominal, subcutaneous, visceral, and mesorectal fatty tissue components were measured semiquantitatively by two radiologists using computed tomography (CT)-based findings. The patients were divided into two groups as those with and without a pathological response to nCRT. The relationship of MRV with the other fat tissue components of the body was also evaluated.

RESULTS

We performed a retrospective analysis of 88 patients (mean age 62.7 years [range, 33-90 years]; 31 males and 57 females). A positive response to nCRT was present in 47 patients. There were 59 patients with stage 3 disease. 46 patients demonstrated lymph node involvement. The mean MRV was 69.6 ± 31.0 ml in no-response group and 105.8 ± 47.5 ml in response-positive patients (p < 0.05). MRV showed the highest correlation with visceral fat volume (VFV). There was a negative correlation between the MRV and the N stage. A cut-off value of ≥ 69.4 for MRV predicted the repsonse to nCRT, with 82.9% sensitivity and 58.5% specificity [AUC: 0.757 (0.653-0.842), p < 0.001] in receiver operating characteristic (ROC) curve analysis CONCLUSIONS: MRV can be used as a novel parameter in predicting of pathological response to nCRT in locally advanced rectal cancer patients.

Vascular calcification and response to neoadjuvant therapy in locally advanced rectal cancer: an exploratory study

Purpose

Patients with locally advanced rectal cancer (LARC) may experience a clinical complete response (cCR) to neoadjuvant chemoradiotherapy (NACRT) and opt for non-operative management. Pathological factors that relate to NACRT response have been well described. Host factors associated with response, however, are poorly defined. Calcification of the aortoiliac (AC) vessels supplying the rectum may influence treatment response.

Methods

Patients with LARC having NACRT prior to curative surgery at Glasgow Royal Infirmary (GRI) and St Mark’s hospital (SMH) between 2008 and 2016 were identified. AC was scored on pre-treatment CT imaging. NACRT response was assessed using pathologic complete response (pCR) rates, tumour regression grades (TRGs), the NeoAdjuvant Rectal score and T-/N-downstaging. Associations were assessed using Chi-squared, Mantel–Haenszel and Fisher’s exact tests.

Results

Of 231 patients from GRI, 79 (34%) underwent NACRT for LARC. Most were male (58%), aged over 65 (51%) with mid- to upper rectal tumours (56%) and clinical T3/4 (95%), node-positive (77%) disease. pCR occurred in 10 patients (13%). Trends were noted between higher clinical T stage and poor response by Royal College of Pathologist’s TRG (p = 0.021) and tumour height > 5 cm and poor response by Mandard TRG (0.068). In the SMH cohort, 49 of 333 (15%) patients underwent NACRT; 8 (16%) developed a pCR. AC was not associated with NACRT response in either cohort.

Conclusions

AC was not associated with NACRT response in this cohort. Larger contemporary cohorts are required to better assess host determinants of NACRT response and develop predictive models to improve patient selection.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00432-021-03570-1.

A field strength independent MR radiomics model to predict pathological complete response in locally advanced rectal cancer

PURPOSE

Aim of this study was to develop a generalised radiomics model for predicting pathological complete response after neoadjuvant chemo-radiotherapy in locally advanced rectal cancer patients using pre-CRT T2-weighted images acquired at a 1.5 T and a 3 T scanner.

METHODS

In two institutions, 195 patients were scanned: 136 patients were scanned on a 1.5 T MR scanner, 59 patients on a 3 T MR scanner. Gross tumour volumes were delineated on the MR images and 496 radiomic features were extracted, applying the intensity-based (IB) filter. Features were standardised with Z-score normalisation and an initial feature selection was carried out using Wilcoxon-Mann-Whitney test: The most significant features at 1.5 T and 3 T were selected as main features. Several logistic regression models combining the main features with a third one selected by those resulting significant were elaborated and evaluated in terms of area under curve (AUC). A tenfold cross-validation was repeated 300 times to evaluate the model robustness.

RESULTS

Three features were selected: maximum fractal dimension with IB = 0-50, energy and grey-level non-uniformity calculated on the run-length matrix with IB = 0-50. The AUC of the model applied to the whole dataset after cross-validation was 0.72, while values of 0.70 and 0.83 were obtained when 1.5 T and 3 T patients were considered, respectively.

CONCLUSIONS

The model elaborated showed good performance, even when data from patients scanned on 1.5 T and 3 T were merged. This shows that magnetic field intensity variability can be overcome by means of selecting appropriate image features.

Rectal cancer with complete endoscopic response after neoadjuvant therapy: what is the meaning of a positive MRI?

OBJECTIVES

To determine the short-term outcomes of discordant tumor assessments between DWI-MRI and endoscopy in patients with treated rectal cancer when tumor-bed diffusion restriction is present ("+DWI").

METHODS

In this HIPPA-compliant, IRB-approved retrospective study, rectal MRI and endoscopic reports were reviewed for patients with locally advanced primary rectal adenocarcinoma (LARC) treated with chemoradiotherapy or total neoadjuvant therapy and imaged between January 2016 and December 2019. Eligible patients had a +DWI and endoscopy within 2 weeks of each other. True positive MRI were those with tumor on endoscopy and/or biopsy (TP^a) or in whom endoscopy was negative for tumor, but subsequent 3-month follow-up endoscopy and DWI were both positive (TP^b). The positive predictive value of DWI-MRI was calculated on a per-scan and per-patient basis. DWI-negative MRI exams were not explored in this study.

RESULTS

In total, 397 patients with nonmetastatic primary LARC were analyzed. After exclusions, 90 patients had 98 follow-up rectal MRI studies with +DWI. Seventy-six patients underwent 80 MRI scans and had concordant findings at endoscopy (TPa). Seventeen patients underwent 18 MRI scans and had discordant findings at endoscopy (FP); among these, 4 scans in 4 patients were initially false positive (FP) but follow-up MRI remained +DWI and the endoscopy turned concordantly positive (TP^b). PPV was 0.86 per scan and per patient. In 4/18 (22%) scans and 4/17 (24%) patients with discordances, MRI detected tumor regrowth before endoscopy.

CONCLUSIONS

Although most +DWI exams discordant with endoscopy are false positive, 22% will reveal that DWI-MRI detects tumor recurrence before endoscopy.

KEY POINTS

• Most often, in post-treatment assessment for rectal cancer when DWI-MRI shows restriction in the tumor bed and endoscopy shows no tumor, +DWI MRI will be proven false positive. • Conversely, our study demonstrated that, allowing for sequential follow-up at a 3-month maximum interval, DWI-MRI may detect tumor presence in the treated tumor bed before endoscopy in 22% of discordant findings between DWI-MRI and endoscopy. • Our results showed that a majority of DWI-MRI-positive scans in treated rectal cancer concur with the presence of tumor on endoscopy performed within 2 weeks.

Predicting poor response to neoadjuvant chemoradiotherapy for locally advanced rectal cancer: Model constructed using pre-treatment MRI features of structured report template

PURPOSE

To develop a predictive model with pre-treatment magnetic resonance imaging (MRI) findings of the structured report template and clinical parameters for poor responses prediction after neoadjuvant chemoradiotherapy (neoCRT) in locally advanced rectal cancers (LARC) patients.

METHOD

Patients with clinicopathologically confirmed LARC (training and validation datasets, n = 100 and 71, respectively) were enrolled. Patients' clinical data were retrospectively collected. MRI findings of the structured report template were analysed. The tumour regression grade (TRG) system as proposed by Mandard et al was used. Poor response was defined as TRG 3-5. Univariate logistic regression analysis and a lasso regression model were performed to select the significant predictive features from the training set. A nomogram was constructed based on a multivariable logistic regression analysis. Calibration, discrimination, and clinical usefulness of the nomogram were assessed. The calibrative and discriminative ability of our model were compared with those of models including the tumour-node-metastasis (TNM) stage and clinical factors.

RESULTS

The MRI-reported T4b stage, MRI-reported extramural venous invasion (EMVI) positivity, MRI-detected number of positive mesorectal lymph nodes (LNs) > 0, and preoperative oxaliplatin and capecitabine (CAPOX) chemotherapy regimen were incorporated into our nomogram. The nomogram showed good discrimination, with areas under the receiver operating characteristic (ROC) curves of 0·823 and 0·820 in the training and test sets, respectively, and good calibration in both datasets. The decision curve analysis confirmed that the nomogram was clinically useful. The calibrative and discriminative ability of our model were better than those models including the TNM stage and clinical factors.

CONCLUSION

A nomogram based on pre-treatment MRI features of the structured report template and clinical risk factors has potential for use as a non-invasive tool to preoperatively predict poor responses in LARC patients after neoCRT.

MRI Evaluation of the Response of Rectal Cancer to Neoadjuvant Chemoradiation Therapy

MRI plays a critical role in the staging and restaging of rectal cancer. Although newly diagnosed early-stage rectal cancers may immediately be amenable to surgical resection, patients with advanced disease first undergo neoadjuvant therapy that consists of a combination of chemotherapy and radiation therapy. Evaluation of rectal cancer after neoadjuvant therapy is best performed with MRI, given its superior soft-tissue contrast and its ability to allow multiplanar imaging and functional evaluation. In this setting, MRI allows accurate evaluation of primary tumor staging, which is determined on the basis of the depth of invasion within and through the rectal wall and the involvement of adjacent organs. MRI can also be used to evaluate posttreatment morphologic components within the tumors, including fibrosis and mucinous changes that have been shown to correlate with the response to treatment. Additional features such as the circumferential resection margin and extramural vascular invasion-factors shown to affect prognosis and local recurrence-are also assessed before and after therapy. Functional assessment with diffusion-weighted MRI and perfusion MRI plays a role in predicting tumor aggressiveness and the likelihood of response to treatment, as well as the extent of residual tumor after therapy. Lymph node staging is also performed at MRI, with assessment of not only lymph node size but also the internal architecture and signal intensity characteristics. ^©RSNA, 2019 See discussion on this article by Wasnik and Al-Hawary .

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 of rectal cancer-repeatability of quantitative data: a feasibility study

PURPOSE

In this study, we aimed to analyze the repeatability of quantitative multiparametric rectal magnetic resonance imaging (MRI) parameters with different measurement techniques.

METHODS

All examinations were performed with 3 T MRI system. In addition to routine sequences for rectal cancer imaging protocol, small field-of-view diffusion-weighted imaging and perfusion sequences were acquired in each patient. Apparent diffusion coefficient (ADC) was used for diffusion analysis and ktrans was used for perfusion analysis. Three different methods were used in measurement of these parameters; measurements were performed twice by one radiologist for intraobserver and separately by three radiologists for interobserver variability analysis. ADC was measured by the lowest value, the value at maximum wall thickness, and freehand techniques. Ktrans was measured at the slice with maximum wall thickness, by freehand drawn region of interest (ROI), and at the dark red spot with maximum value.

RESULTS

A total of 30 patients with biopsy-proven rectal adenocarcinoma were included in the study. The mean values of the parameters measured by the first radiologist on the first and second measurements were as follows: mean lowest ADC, 721.31±147.18 mm2/s and 718.96±135.71 mm2/s; mean ADC value on the slice with maximum wall thickness, 829.90±144.24 mm2/s and 829.48±149.23 mm2/s; mean ADC value measured by freehand ROI on the slice with maximum wall thickness, 846.56±136.31 mm2/s and 848.23±144.15 mm2/s; mean ktrans value on the slice with maximum wall thickness, 0.219±0.080 and 0.214±0.074; mean ktrans by freehand ROI technique (including as much tumoral tissue as possible), 0.208±0.074 and 0.207±0.069; mean ktrans measured from the dark red foci, 0.308±0.109 and 0.311±0.105. Intraobserver agreement was very good among diffusion and perfusion parameters obtained with all three measurement techniques. Interobserver agreement was very good, except for one of the measurement techniques. As far as interobserver variability is considered, only ADC value measured on the slice with maximum wall thickness differed significantly.

CONCLUSION

Multiparametric MRI of rectum, using ADC as the diffusion and ktrans as the perfusion parameter is a repeatable technique. This technique may potentially be used in prediction and evaluation of neoadjuvant treatment response. New studies with larger patient groups are needed to validate the role of multiparametric MRI.

Dynamic contrast-enhanced MR imaging of rectal cancer using a golden-angle radial stack-of-stars VIBE sequence: comparison with conventional contrast-enhanced 3D VIBE sequence

PURPOSE

To compare conventional 3D volumetric-interpolated breath-hold examination (C-VIBE) sequence image quality to that of golden-angle radial stack-of stars acquisition scheme (R-VIBE) in rectal cancer patients.

METHODS

Seventy-eight patients had undergone pre-contrast C-VIBE, followed by DCE-MRI with R-VIBE and post-contrast C-VIBE in the visualization of rectal cancer. The first phase and the last phase of R-VIBE sequence were compared with pre-contrast and post-contrast C-VIBE sequences, respectively. Signal-to-noise ratios (SNRs) and contrast-to-noise ratios (CNRs) of rectal neoplasms, gluteus maximus, and subcutaneous fat were compared between the two different sequences. A further qualitative score system (graded 1-5) was used to evaluate the overall image. Quantitative and qualitative parameters from the two sequences were compared.

RESULTS

In all patients, R-VIBE achieved the same SNR and CNR ratings in pre- and post-contrast (all P > 0.05), with the exception of a higher SNR of fat in pre-contrast images (P = 0.037). In addition, there were no significant differences in scores of overall image quality, lesion conspicuity, and rectal wall boundary (all P > 0.05). There was an improved score in artifacts of post-contrast R-VIBE sequence (P = 0.005).

CONCLUSION

R-VIBE sequence can provide comparable image quality and less motion artifacts to that of C-VIBE sequence and is feasible for imaging of rectal cancer.

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.

Long Term Results of Modified Intersphincteric Resections for Low Rectal Cancer: A Single Center Experience

BACKGROUND AND OBJECTIVES

The objective of this article is to evaluate the long-term oncological and functional outcomes following modified intersphincteric resections (ISR) for low rectal cancer. The modified technique consisted of the abandonment of colonic J-pouches, transverse coloplasty, or defunctioning temporary stoma in favor of a direct handsewn coloanal anastomosis (CAA).

MATERIAL AND METHODS

Sixty consecutive patients with type II and III (juxta-anal or intra-anal) low rectal tumors underwent modified ISR by the same surgical team and were followed for a period of five years. Functional outcomes using the Wexner Score, postoperative complications, recurrence rates, morbidity, and mortality rates were assessed.

RESULTS

The five-year survival rate was 93.3% with a disease-free interval at three years of 98%. Morbidity was 15% (n = 9) consisting of intestinal wall necrosis (n = 6), stenosis (n = 2), and sacral metastasis (n = 1). The Wexner score values were, at 1 year, 8.5 (range, 4-13); at three years 7.2 (range, 2-11); and at 5 years 6.7 (range, 2-12). A second surgery was needed in only one case that showed postoperative transmural necrosis of the colonic wall.

CONCLUSIONS

In highly selected patients with type II or III low rectal tumors and proper preoperative imaging staging, ISR might be a viable alternative to other techniques such as abdominoperineal resection and low anterior resection, both from a functional and an oncological perspective.

Rectal Cancer: Staging

The imaging of rectal cancer has evolved noticeably over the past 2 decades, paralleling the advances in therapy. The methods for imaging rectal cancer are increasingly used in clinical practice with the purpose of helping to detect, characterize and stage rectal cancer. In this setting, MR imaging emerged as the most useful imaging method for primary staging of rectal cancer; the present review focuses on the role of MR imaging in this regard.

Diagnostic performance of magnetic resonance to assess treatment response after neoadjuvant therapy in patients with locally advanced rectal cancer

PURPOSE

Our study aimed to evaluate the diagnostic performance of rectal magnetic resonance imaging (MRI) for local restaging in patients with non-metastatic locally advanced rectal cancer (LARC) after neoadjuvant chemoradiotherapy (CRT) using surgical histopathology of total mesorectal excision as the reference standard.

METHODS

Ninety-five patients with LARC who underwent rectal MRI after CRT between January 2014 and December 2016 were included. Accuracy, sensitivity, specificity, positive, and negative predictive value for local staging regarding T-stage, N-stage, circumferential resection margin, and MRI tumor regression grade (ymriTRG) were calculated, and inter-test agreements were assessed.

RESULTS

22/95 (23.2%) patients had radiological complete response (rCR), whereas 20/95 (21.1%) had pathological complete response (pCR). Among the patients with pCR, 11/20 (55%) had rCR. Fair agreement was demonstrated between ymriTRG and pathological TRG (ypTRG) (κ = 0.255). The sensitivity and specificity for detection of pCR were 61.1% (95% CI 35.7-82.7) and 89.6% (95% CI 80.6-95.4). For the detection of ypTRG grades 1 and 2, the corresponding values were 67.2% (95% CI 54.3-78.4) and 51.6 (95% CI 33.1-69.8). The accuracy of ymriTRG was 24.2% (95% CI 15.6-32.8). Inter-test agreement in TRG between MRI and pathology was overall fair (κ = 0.255) and slight (κ = 0.179), if TRG 1 + 2.

CONCLUSION

Qualitative assessment on MRI for diagnosing pCR showed moderate sensitivity and high specificity, whereas the diagnosis of TRG had moderate sensitivity and low specificity with slight to fair inter-test agreement when compared with pathological specimens.

Developing a prediction model based on MRI for pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer

PURPOSE

The aim of this study was to build an appropriate diagnostic model for predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC), by combining magnetic resonance imaging (MRI) parameters with clinical factors.

METHODS

Eighty-four patients with LARC who underwent MR examination before and after nCRT were enrolled in this study. MRI parameters including cylindrical approximated tumor volume (CATV) and relative signal intensity of tumor (rT2wSI) were measured; corresponding reduction rates (RR) were calculated; and MR tumor regression grade (mrTRG) and other conventional MRI parameters were assessed. Logistic regression with lasso regularization was performed and the appropriate prediction model for pCR was built up. An external cohort of thirty-six patients was used as the validation group for testing the model. Receiver-operating characteristic (ROC) analysis was used to assess the diagnostic performance.

RESULTS

In the development and the validation group, 17 patients (20.2%) and 11 patients (30.6%), respectively, achieved pCR. Two CATV-related parameters (CATVpost, which is the CATV measured after nCRT and CATVRR), one rT2wSI-related parameter (rT2wSIRR), and mrTRG were the most important parameters for predicting pCR and were retained in the diagnostic model. In the development group, the area under the receiver-operating characteristic curve (AUC) for predicting pCR is 0.88 [95% confidence interval (CI) 0.78-0.97, p < 0.001], with a sensitivity of 82.4% and a specificity of 83.6%. In the validation group, the AUC is 0.84 (95% CI 0.70-0.98, p = 0.001), with a sensitivity of 81.8% and a specificity of 76.0%.

CONCLUSION

A diagnostic model including CATVpost, CATVRR, rT2wSIRR, and mrTRG was useful for predicting pCR after nCRT in patients with LARC and may be used as an effective organ-preservation strategy.

Validated imaging biomarkers as decision-making tools in clinical trials and routine practice: current status and recommendations from the EIBALL* subcommittee of the European Society of Radiology (ESR)

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions.

Dynamic contrast-enhanced magnetic resonance imaging in locally advanced rectal cancer: role of perfusion parameters in the assessment of response to treatment

PURPOSE

To correlate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters to tumor grading and to assess their reliability in predicting pathological complete response (pCR) before neoadjuvant chemoradiotherapy (CRT) in patients with locally advanced rectal cancer (LARC).

MATERIALS AND METHODS

Forty patients (24 male; mean age, 67.3 ± 8.1 years) with histologically proven LARC who had undergone 3-Tesla DCE-MRI before (MRI_1) and after CRT (MRI_2) between August 2015 and February 2016 were included in this retrospective study. DCE-MRI parameters at MRI_1 and MRI_2 were extracted by two board certified radiologists in consensus reading with Olea Sphere 2.3 software using the extended Tofts model. Based on DCE-MRI results, patients were divided in complete responders (CR) and non-complete responders (nCR) and the perfusion parameters were correlated to tumor grading and pCR.

RESULTS

Wash-out and K_ep at MRI_1 showed significant correlation with LARC grading (P = 0.004 and 0.01, respectively). V_e showed a significant increase between MRI_1 (0.47 ± 0.27) and MRI_2 (0.63 ± 0.23; P = 0.007). K_trans measured at MRI_1 was significantly higher in CR (0.66 ± 0.48) compared to nCR (0.53 ± 0.34, P = 0.02).

CONCLUSION

Wash-out and K_ep measured before CRT correlate with LARC grading. V_e changes during CRT, while K_trans measured before CRT may predict the response to therapy. Therefore, DCE-MRI parameters can predict tumor aggressiveness and CRT efficacy, playing a role as imaging biomarkers in patients with LARC.

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.

Value of adding dynamic contrast-enhanced MRI visual assessment to conventional MRI and clinical assessment in the diagnosis of complete tumour response to chemoradiotherapy for rectal cancer

PURPOSE

To determine if DCE-MRI adds diagnostic value to the combined use of T2WI and DWI-MRI in the determination of clinical complete response (cCR) after neoadjuvant treatment (NAT) in patients with locally advanced rectal cancer.

METHODS AND MATERIALS

In this IRB-approved, HIPAA-compliant retrospective study, response was assessed using a 5-point confidence score by T2WI and DWI-MRI only ('standard MRI'), then with addition of DCE-MRI. Review of digital rectal exams and endoscopy notes produced a clinical overall response score. The reference standard was CR by histopathology or cCR determined after a minimum of 18 months' follow-up. Diagnostic accuracy and ROC curves were calculated for standard MRI and added DCE-MRI (to detect complete or good response), for clinical evaluation (to detect CR) and for MRI and clinical methods combined.

RESULTS

Of 65 patients undergoing NAT, 20 had cCR (31%). Sensitivity, specificity and area under the ROC (AUC) were 0.55, 0.87 and 0.69 for clinical evaluation; 0.42, 0.77 and 0.66 for standard MRI, and 0.53, 0.76 and 0.68 for added DCE-MRI, respectively. Combined clinical evaluation and standard MRI with DCE-MRI resulted in the highest specificity of 0.96 and highest AUC of 0.72.

CONCLUSION

For the assessment of cCR after neoadjuvant therapy using clinical and multi-sequence MRI reading strategies, the addition of DCE-MRI increased specificity and PPV, but not significantly.

KEY POINTS

• The addition of dynamic contrast-enhanced MRI to standard MRI, including DWI-MRI, may not significantly improve accuracy of response assessment in rectal cancer treatment. • Clinical assessment consisting of digital rectal examination and endoscopy is the most accurate standalone test to assess response to chemoradiotherapy in rectal cancer. • Combining MRI using DWI and DCE with the clinical assessment may potentially improve the accuracy for response assessment in rectal cancer.

Quantitating whole lesion tumor biology in rectal cancer MRI: taking a lesson from FDG-PET tumor metrics

PURPOSE

To determine the value of novel whole tumor metrics in DWI-MRI and DCE-MRI of rectal cancer treatment assessment.

MATERIALS AND METHODS

This retrospective study included 24 uniformly treated patients with rectal adenocarcinoma who underwent MRI including diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) sequences, before and after chemoradiotherapy. Two experienced readers independently measured tumor volume and apparent diffusion coefficient (ADC) on DWI-MRI and tumor volume and transfer constant K trans on DCE-MRI. In addition, we explored and defined Total Lesion Diffusion (TLD) as Total DWI tumor volume multiplied by mean volumetric ADC and Total Lesion Perfusion (TLP) as the total DCE tumor volume multiplied by the mean volumetric K trans. These metrics were correlated with histopathologic percent tumor regression in the resected specimen (%TR). Inter-reader agreement was assessed using the concordance correlation coefficient (CCC).

RESULTS

For both readers, post-treatment TLP revealed comparable correlations with %TR compared with K trans (reader 1; Spearman's rho = - 0.36 vs. - 0.32, reader 2; Spearman's rho = - 0.32 vs. - 0.28). In addition, TLP afforded the highest inter-reader agreement at post-treatment among TLP, DCE vol, and K trans (CCC: 0.64 vs. 0.36 vs. 0.35). Post-treatment TLD showed similar correlation with %TR as DWI volume in reader 1 and superior correlation with %TR for reader 2 (reader 1; Spearman's rho - 0.56 vs. - 0.57, reader 2; Spearman's rho - 0.59 vs. - 0.45).

CONCLUSION

The novel tumor metrics TLD and TLP revealed similar results to established metrics for correlation with tumor response with equivalent or superior inter-reader agreements and we recommend that these be studied in larger trials.

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.

T2-weighted signal intensity-selected volumetry for prediction of pathological complete response after preoperative chemoradiotherapy in locally advanced rectal cancer

OBJECTIVES

To evaluate the diagnostic value of signal intensity (SI)-selected volumetry findings in T2-weighted magnetic resonance imaging (MRI) as a potential biomarker for predicting pathological complete response (pCR) to preoperative chemoradiotherapy (CRT) in patients with rectal cancer.

METHODS

Forty consecutive patients with pCR after preoperative CRT were compared with 80 age- and sex-matched non-pCR patients in a case-control study. SI-selected tumor volume was measured on post-CRT T2-weighted MRI, which included voxels of the treated tumor exceeding the SI (obturator internus muscle SI + [ischiorectal fossa fat SI - obturator internus muscle SI] × 0.2). Three blinded readers independently rated five-point pCR confidence scores and compared the diagnostic outcome with SI-selected volumetry findings. The SI-selected volumetry protocol was validated in 30 additional rectal cancer patients.

RESULTS

The area under the receiver-operating characteristic curve (AUC) of SI-selected volumetry for pCR prediction was 0.831, with an optimal cutoff value of 649.6 mm³ (sensitivity 0.850, specificity 0.725). The AUC of the SI-selected tumor volume was significantly greater than the pooled AUC of readers (0.707, p < 0.001). At this cutoff, the validation trial yielded an accuracy of 0.87.

CONCLUSION

SI-selected volumetry in post-CRT T2-weighted MRI can help predict pCR after preoperative CRT in patients with rectal cancer.

KEY POINTS

• Fibrosis and viable tumor MRI signal intensities (SIs) are difficult to distinguish. • T2 SI-selected volumetry yields high diagnostic performance for assessing pathological complete response. • T2 SI-selected volumetry is significantly more accurate than readers and non-SI-selected volumetry. • Post-chemoradiation therapy T2-weighted MRI SI-selected volumetry facilitates prediction of pathological complete response.

Variability and Reproducibility of 3rd-generation dual-source dynamic volume perfusion CT Parameters in Comparison to MR-perfusion Parameters in Rectal Cancer

To compare in patients with untreated rectal cancer quantitative perfusion parameters calculated from 3^rd-generation dual-source dynamic volume perfusion CT (dVPCT) with 3-Tesla-MR-perfusion with regard to data variability and tumour differentiation. In MR-perfusion, plasma flow (PF), plasma volume (PV) and mean transit time (MTT) were assessed in two measurements (M1 and M2) by the same reader. In dVPCT, blood flow (BF), blood volume (BV), MTT and permeability (PERM) were assessed respectively. CT dose values were calculated. 20 patients (60 ± 13 years) were analysed. Intra-individual and intra-reader variability of duplicate MR-perfusion measurements was higher compared to duplicate dVPCT measurements. dVPCT-derived BF, BV and PERM could differentiate between tumour and normal rectal wall (significance level for M1 and M2, respectively, regarding BF: p < 0.0001*/0.0001*; BV: p < 0.0001*/0.0001*; MTT: p = 0.93/0.39; PERM: p < 0.0001*/0.0001*), with MR-perfusion this was true for PF and PV (p-values M1/M2 for PF: p = 0.04*/0.01*; PV: p = 0.002*/0.003*; MTT: p = 0.70/0.27*). Mean effective dose of CT-staging incl. dVPCT was 29 ± 6 mSv (20 ± 5 mSv for dVPCT alone). In conclusion, dVPCT has a lower data variability than MR-perfusion while both dVPCT and MR-perfusion could differentiate tumour tissue from normal rectal wall. With 3^rd-generation dual-source CT dVPCT could be included in a standard CT-staging without exceeding national dose reference values.

Assessment of response to chemotherapy in pancreatic ductal adenocarcinoma: Comparison between diffusion-weighted MR quantitative parameters and RECIST

PURPOSE

To prospectively assess chemotherapy-induced changes in pancreatic ductal adenocarcinoma (PDA) with diffusion-weighted (DW)-MR quantitative metrics, including apparent diffusion coefficient (ADC) and histogram-derived parameters, compared with RECIST 1.1.

METHODS

24 patients underwent DW-MR at baseline, week-2 and week-8 after chemotherapy initiation. Tumour diameter was assessed on T2-weighted images. Regions-of-interest (ROI) were drawn on ADC map for ROI-ADC. Volume segmentation (b = 1000 s/mm² images) provided DW-volume and histogram-derived diffusion parameters (H-ADC, H-D and H-PF). All variables and their relative change were compared to baseline or between responders and non-responders. Discriminant analysis was performed.

RESULTS

15/24 patients were responders. RECIST 1.1 correctly characterized 6/15 responders at week-8. At week-2, in responders DW-volume decreased (P = .002); ROI-ADC mean H-D increased (P = .047; P = .048;). The 25th percentile H-D increased in responders and decreased in non-responders (P = .016; P = .048). At week-8 in responders DW-volume decreased and ROI-ADC mean, 25th, 50th, 75th percentiles of H-ADC and H-D increased (P < .05). No changes were observed in non-responders (P > .05). At week-2, 25th percentile of H-D and H-PF relative change correctly classified 20/24 patients (P = .003); at week-8, DW-volume relative change correctly classified 22/24 patients (P < .0001).

CONCLUSIONS

ROI-ADC, DW-volume and histogram-derived diffusion parameters are more accurate to categorize responding and non-responding PDA patients treated with chemotherapy compared with RECIST 1.1.

Advanced Imaging Techniques in Evaluation of Colorectal Cancer

Imaging techniques are clinical decision-making tools in the evaluation of patients with colorectal cancer (CRC). The aim of this article is to discuss the potential of recent advances in imaging for diagnosis, prognosis, therapy planning, and assessment of response to treatment of CRC. Recent developments and new clinical applications of conventional imaging techniques such as virtual colonoscopy, dual-energy spectral computed tomography, elastography, advanced computing techniques (including volumetric rendering techniques and machine learning), magnetic resonance (MR) imaging-based magnetization transfer, and new liver imaging techniques, which may offer additional clinical information in patients with CRC, are summarized. In addition, the clinical value of functional and molecular imaging techniques such as diffusion-weighted MR imaging, dynamic contrast material-enhanced imaging, blood oxygen level-dependent imaging, lymphography with contrast agents, positron emission tomography with different radiotracers, and MR spectroscopy is reviewed, and the advantages and disadvantages of these modalities are evaluated. Finally, the future role of imaging-based analysis of tumor heterogeneity and multiparametric imaging, the development of radiomics and radiogenomics, and future challenges for imaging of patients with CRC are discussed. Online supplemental material is available for this article. ^©RSNA, 2018.

MR Imaging of Rectal Cancer: Radiomics Analysis to Assess Treatment Response after Neoadjuvant Therapy

Purpose To investigate the value of T2-weighted-based radiomics compared with qualitative assessment at T2-weighted imaging and diffusion-weighted (DW) imaging for diagnosis of clinical complete response in patients with rectal cancer after neoadjuvant chemotherapy-radiation therapy (CRT). Materials and Methods This retrospective study included 114 patients with rectal cancer who underwent magnetic resonance (MR) imaging after CRT between March 2012 and February 2016. Median age among women (47 of 114, 41%) was 55.9 years (interquartile range, 45.4-66.7 years) and median age among men (67 of 114, 59%) was 55 years (interquartile range, 48-67 years). Surgical histopathologic analysis was the reference standard for pathologic complete response (pCR). For qualitative assessment, two radiologists reached a consensus. For radiomics, one radiologist segmented the volume of interest on high-spatial-resolution T2-weighted images. A random forest classifier was trained to separate the patients by their outcomes after balancing the number of patients in each response category by using the synthetic minority oversampling technique. Statistical analysis was performed by using the Wilcoxon rank-sum test, McNemar test, and Benjamini-Hochberg method. Results Twenty-one of 114 patients (18%) achieved pCR. The radiomic classifier demonstrated an area under the curve of 0.93 (95% confidence interval [CI]: 0.87, 0.96), sensitivity of 100% (95% CI: 0.84, 1), specificity of 91% (95% CI: 0.84, 0.96), positive predictive value of 72% (95% CI: 0.53, 0.87), and negative predictive value of 100% (95% CI: 0.96, 1). The diagnostic performance of radiomics was significantly higher than was qualitative assessment at T2-weighted imaging or DW imaging alone (P < .02). The specificity and positive predictive values were significantly higher in radiomics than were at combined T2-weighted and DW imaging (P < .0001). Conclusion T2-weighted-based radiomics showed better classification performance compared with qualitative assessment at T2-weighted and DW imaging for diagnosing pCR in patients with locally advanced rectal cancer after CRT. ^© RSNA, 2018 Online supplemental material is available for this article.

Haralick's texture features for the prediction of response to therapy in colorectal cancer: a preliminary study

PURPOSE

Haralick features Texture analysis is a recent oncologic imaging biomarker used to assess quantitatively the heterogeneity within a tumor. The aim of this study is to evaluate which Haralick's features are the most feasible in predicting tumor response to neoadjuvant chemoradiotherapy (CRT) in colorectal cancer.

MATERIALS AND METHODS

After MRI and histological assessment, eight patients were enrolled and divided into two groups based on response to neoadjuvant CRT in complete responders (CR) and non-responders (NR). Oblique Axial T2-weighted MRI sequences before CRT were analyzed by two radiologists in consensus drawing a ROI around the tumor. 14 over 192 Haralick's features were extrapolated from normalized gray-level co-occurrence matrix in four different directions. A dedicated statistical analysis was performed to evaluate distribution of the extracted Haralick's features computing mean and standard deviation.

RESULTS

Pretreatment MRI examination showed significant value (p < 0.05) of 5 over 14 computed Haralick texture. In particular, the significant features are the following: concerning energy, contrast, correlation, entropy and inverse difference moment.

CONCLUSIONS

Five Haralick's features showed significant relevance in the prediction of response to therapy in colorectal cancer and might be used as additional imaging biomarker in the oncologic management of colorectal patients.

Magnetic resonance imaging for clinical management of rectal cancer: Updated recommendations from the 2016 European Society of Gastrointestinal and Abdominal Radiology (ESGAR) consensus meeting

OBJECTIVES

To update the 2012 ESGAR consensus guidelines on the acquisition, interpretation and reporting of magnetic resonance imaging (MRI) for clinical staging and restaging of rectal cancer.

METHODS

Fourteen abdominal imaging experts from the European Society of Gastrointestinal and Abdominal Radiology (ESGAR) participated in a consensus meeting, organised according to an adaptation of the RAND-UCLA Appropriateness Method. Two independent (non-voting) Chairs facilitated the meeting. 246 items were scored (comprising 229 items from the previous 2012 consensus and 17 additional items) and classified as 'appropriate' or 'inappropriate' (defined by ≥ 80 % consensus) or uncertain (defined by < 80 % consensus).

RESULTS

Consensus was reached for 226 (92 %) of items. From these recommendations regarding hardware, patient preparation, imaging sequences and acquisition, criteria for MR imaging evaluation and reporting structure were constructed. The main additions to the 2012 consensus include recommendations regarding use of diffusion-weighted imaging, criteria for nodal staging and a recommended structured report template.

CONCLUSIONS

These updated expert consensus recommendations should be used as clinical guidelines for primary staging and restaging of rectal cancer using MRI.

KEY POINTS

• These guidelines present recommendations for staging and reporting of rectal cancer. • The guidelines were constructed through consensus amongst 14 pelvic imaging experts. • Consensus was reached by the experts for 92 % of the 246 items discussed. • Practical guidelines for nodal staging are proposed. • A structured reporting template is presented.

Optimising preoperative risk stratification tools for prostate cancer using mpMRI

Purpose

To improve preoperative risk stratification for prostate cancer (PCa) by incorporating multiparametric MRI (mpMRI) features into risk stratification tools for PCa, CAPRA and D’Amico.

Methods

807 consecutive patients operated on by robot-assisted radical prostatectomy at our institution during the period 2010–2015 were followed to identify biochemical recurrence (BCR). 591 patients were eligible for final analysis. We employed stepwise backward likelihood methodology and penalised Cox cross-validation to identify the most significant predictors of BCR including mpMRI features. mpMRI features were then integrated into image-adjusted (IA) risk prediction models and the two risk prediction tools were then evaluated both with and without image adjustment using receiver operating characteristics, survival and decision curve analyses.

Results

37 patients suffered BCR. Apparent diffusion coefficient (ADC) and radiological extraprostatic extension (rEPE) from mpMRI were both significant predictors of BCR. Both IA prediction models reallocated more than 20% of intermediate-risk patients to the low-risk group, reducing their estimated cumulative BCR risk from approximately 5% to 1.1%. Both IA models showed improved prognostic performance with a better separation of the survival curves.

Conclusion

Integrating ADC and rEPE from mpMRI of the prostate into risk stratification tools improves preoperative risk estimation for BCR.

Key points

• MRI-derived features, ADC and EPE, improve risk stratification of biochemical recurrence.

• Using mpMRI to stratify prostate cancer patients improves the differentiation between risk groups.

• Using preoperative mpMRI will help urologists in selecting the most appropriate treatment.

Electronic supplementary material

The online version of this article (10.1007/s00330-017-5031-5) contains supplementary material, which is available to authorized users.