Value of DCE-MRI for staging and response evaluation in rectal cancer: A systematic review

Discriminating Tumor Deposits From Metastatic Lymph Nodes in Rectal Cancer: A Pilot Study Utilizing Dynamic Contrast-Enhanced MRI

OBJECTIVE

To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer.

MATERIALS AND METHODS

A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (Ktrans, kep, and ve) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups. Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs.

RESULTS

All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, ve had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, ve, and ADCmean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027).

CONCLUSION

The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

What is the predictive value of pretreatment MRI characteristics for achieving a complete response after total neoadjuvant treatment in locally advanced rectal cancer?

OBJECTIVES

To investigate the value of pretreatment magnetic resonance imaging (MRI) features in predicting a complete response to total neoadjuvant treatment (TNT) in locally advanced rectal cancer (LARC).

METHODS

The data of patients who received TNT were analyzed retrospectively. MRI features, including T stage, morphology, length, and volume; the presence of MR-detected extramural venous invasion (mrEMVI), the number of mrEMVI, and the diameter of the largest invaded vein; main vein mrEMVI; presence of MR-detected tumor deposits (mrTDs), the number of mrTDs, and the size of the largest mrTD; MR-detected lymph node status (mrLN); tumor distance from the anal verge; mesorectal fascia involvement (mrMRF + ); and mean apparent diffusion coefficient (ADC) values were recorded. Patients were classified as complete (CRs) or noncomplete responders (non-CRs) according to the pathological/clinical outcomes. For patients managed nonoperatively, a sustained clinical complete response for > 2 years was deemed a surrogate endpoint for complete response. The MRI parameters were categorized into three distinct groups: baseline, advanced, and quantitative features, and were analyzed using multivariable stepwise logistic regression. The ability to predict complete response was evaluated by comparing different combinations of MRI parameters, and performance on an "independent" dataset was estimated using bootstrapped leave-one-out cross-validation (LOOCV).

RESULTS

The data of 84 patients were evaluated (CRs, n = 44; non-CRs, n = 40). The optimal model, which included baseline and quantitative MRI features, achieved an area under the curve of 0.837 for predicting complete response. Selected predictors were T stage and ADC mean value. Advanced MRI features did not improve the performance of the model.

CONCLUSION

A multivariable model combining T stage and the ADC mean value can help identify LARC patients who are likely to a achieve complete response before the initiation of TNT.

Comparative effectiveness of two abbreviated rectal MRI protocols in assessing tumor response to neoadjuvant chemoradiotherapy in patients with rectal cancer

The present study aimed to compare the effectiveness of two abbreviated magnetic resonance imaging (MRI) protocols in assessing the response to neoadjuvant chemoradiotherapy (CRT) in patients with rectal cancer. Data from the examinations of 62 patients with rectal cancer who underwent neoadjuvant CRT and standard contrast-enhanced rectal MRI were retrospectively evaluated. Standard contrast-enhanced T2-weighted imaging (T2-WI), post-contrast T1-weighted imaging (T1-WI) and diffusion-weighted imaging (DWI) MRI, as well as two abbreviated protocols derived from these images, namely protocol AB1 (T2-WI and DWI) and protocol AB2 (post-contrast fat-suppressed (FS) T1-WI and DWI), were assessed. Measurements of lesion length and width, lymph node short-axis length, tumor staging, circumferential resection margin (CRM), presence of extramural venous invasion (EMVI), luminal mucin accumulation (MAIN), mucinous response, mesorectal fascia (MRF) involvement, and MRI-based tumor regression grade (mrTRG) were obtained. The reliability and compatibility of the AB1 and AB2 protocols in the evaluation of tumor response were analyzed. The imaging performed according to the AB1 and AB2 protocols revealed significant decreases in lesion length, width and lymph node size after CRT. These protocols also showed reductions in lymph node positivity, CRM, MRF, EMVI.Furthermore, both protocols were found to be reliable in determining lesion length and width. Additionally, compliance was observed between the protocols in determining lymph node size and positivity, CRM involvement, and EMVI after CRT. In conclusion, the use of abbreviated MRI protocols, specifically T2-WI with DWI sequences or post-contrast FS T1-WI with DWI sequences, is effective for evaluating tumor response in patients with rectal cancer following neoadjuvant CRT. The AB protocols examined in this study yielded similar results in terms of lesion length and width, lymph node positivity, CRM involvement, EMVI, MAIN, and MRF involvement.

The Role of Predictive and Prognostic MRI-Based Biomarkers in the Era of Total Neoadjuvant Treatment in Rectal Cancer

The role of magnetic resonance imaging (MRI) in rectal cancer management has significantly increased over the last decade, in line with more personalized treatment approaches. Total neoadjuvant treatment (TNT) plays a pivotal role in the shift from traditional surgical approach to non-surgical approaches such as 'watch-and-wait'. MRI plays a central role in this evolving landscape, providing essential morphological and functional data that support clinical decision-making. Key MRI-based biomarkers, including circumferential resection margin (CRM), extramural venous invasion (EMVI), tumour deposits, diffusion-weighted imaging (DWI), and MRI tumour regression grade (mrTRG), have proven valuable for staging, response assessment, and patient prognosis. Functional imaging techniques, such as dynamic contrast-enhanced MRI (DCE-MRI), alongside emerging biomarkers derived from radiomics and artificial intelligence (AI) have the potential to transform rectal cancer management offering data that enhance T and N staging, histopathological characterization, prediction of treatment response, recurrence detection, and identification of genomic features. This review outlines validated morphological and functional MRI-derived biomarkers with both prognostic and predictive significance, while also exploring the potential of radiomics and artificial intelligence in rectal cancer management. Furthermore, we discuss the role of rectal MRI in the 'watch-and-wait' approach, highlighting important practical aspects in selecting patients for non-surgical management.

Quantitative Perfusion-Weighted Magnetic Resonance Imaging in Uveal Melanoma

Purpose

Perfusion-weighted imaging (PWI; magnetic resonance imaging [MRI]) has been shown to provide valuable biological tumor information in uveal melanoma (UM). Clinically used semiquantitative methods do not account for tumor pigmentation and eye movement. We hypothesize that a quantitative PWI method that incorporates these, provides a more accurate description of tumor perfusion than the current clinical method. The aim of this study was to test this in patients with UM before and after radiotherapy.

Methods

Perfusion-weighted 3T MRIs were retrospectively analyzed in 47 patients with UM before and after radiotherapy. Tofts pharmacokinetic modeling was performed to determine vascular permeability (Ktrans), extracellular extravascular space (ve), and reflux rate (kep). These were compared with semiquantitative clinical parameters including peak intensity and outflow percentage.

Results

The effect of tumor pigmentation on peak intensity and outflow percentage was statistically significant (P < 0.01) and relative peak intensity was significantly different between melanotic and amelanotic tumors (1.5 vs. 1.9, P < 0.01). Before radiotherapy, median tumor Ktrans was 0.63 min-1 (range = 0.06-1.42 min-1), median ve was 0.23 (range = 0.09-0.63), and median kep was 2.3 min-1 (range = 0.6-5.0 min-1). After radiotherapy, 85% showed a decrease in Ktrans and kep (P < 0.01). Changes in tumor pigmentation before and after radiotherapy were small and not significant (median increase in T1 of 33 ms, P = 0.55).

Conclusions

Quantitative PWI parameters decreased significantly after radiotherapy and can therefore can serve as an early biomarker for treatment response assessment. However, due to the nonsignificant changes in tumor pigmentation before and after radiotherapy, the current semiquantitative method appears to be sufficiently sensitive for detection of changes in tumor perfusion.

Predictive potential of dynamic contrast-enhanced MRI and plasma-derived angiogenic factors for response to concurrent chemoradiotherapy in human papillomavirus-negative oropharyngeal cancer

BACKGROUND

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can assess tumour vascularity, which depends on the process of angiogenesis and affects tumour response to treatment. Our study explored the associations between DCE-MRI parameters and the expression of plasma angiogenic factors in human papilloma virus (HPV)-negative oropharyngeal cancer, as well as their predictive value for response to concurrent chemoradiotherapy (cCRT).

PATIENTS AND METHODS

Twenty-five patients with locally advanced HPV-negative oropharyngeal carcinoma were prospectively enrolled in the study. DCE-MRI and blood plasma sampling were conducted before cCRT, after receiving a radiation dose of 20 Gy, and after the completion of cCRT. Perfusion parameters ktrans, kep, Ve, initial area under the curve (iAUC) and plasma expression levels of angiogenic factors (vascular endothelial growth factor [VEGF], connective tissue growth factor [CTGF], platelet-derived growth factor [PDGF]-AB, angiogenin [ANG], endostatin [END] and thrombospondin-1 [THBS1]) were measured at each time-point. Patients were stratified into responders and non-responders based on clinical evaluation. Differences and correlations between measures were used to generate prognostic models for response prediction.

RESULTS

Higher perfusion parameter ktrans and higher plasma VEGF levels successfully discriminated responders from non-responders across all measured time-points, whereas higher iAUC and higher plasma PDGF-AB levels were also discriminative at selected time points. Using early intra-treatment measurements of ktrans and VEGF, a predictive model was created with cut-off values of 0.259 min-1 for ktrans and 62.5 pg/mL for plasma VEGF.

CONCLUSIONS

Early intra-treatment DCE-MRI parameter ktrans and plasma VEGF levels may be valuable early predictors of response to cCRT in HPV-negative oropharyngeal cancer.

Intraoperative near infrared functional imaging of rectal cancer using artificial intelligence methods - now and near future state of the art

Colorectal cancer remains a major cause of cancer death and morbidity worldwide. Surgery is a major treatment modality for primary and, increasingly, secondary curative therapy. However, with more patients being diagnosed with early stage and premalignant disease manifesting as large polyps, greater accuracy in diagnostic and therapeutic precision is needed right from the time of first endoscopic encounter. Rapid advancements in the field of artificial intelligence (AI), coupled with widespread availability of near infrared imaging (currently based around indocyanine green (ICG)) can enable colonoscopic tissue classification and prognostic stratification for significant polyps, in a similar manner to contemporary dynamic radiological perfusion imaging but with the advantage of being able to do so directly within interventional procedural time frames. It can provide an explainable method for immediate digital biopsies that could guide or even replace traditional forceps biopsies and provide guidance re margins (both areas where current practice is only approximately 80% accurate prior to definitive excision). Here, we discuss the concept and practice of AI enhanced ICG perfusion analysis for rectal cancer surgery while highlighting recent and essential near-future advancements. These include breakthrough developments in computer vision and time series analysis that allow for real-time quantification and classification of fluorescent perfusion signals of rectal cancer tissue intraoperatively that accurately distinguish between normal, benign, and malignant tissues in situ endoscopically, which are now undergoing international prospective validation (the Horizon Europe CLASSICA study). Next stage advancements may include detailed digital characterisation of small rectal malignancy based on intraoperative assessment of specific intratumoral fluorescent signal pattern. This could include T staging and intratumoral molecular process profiling (e.g. regarding angiogenesis, differentiation, inflammatory component, and tumour to stroma ratio) with the potential to accurately predict the microscopic local response to nonsurgical treatment enabling personalised therapy via decision support tools. Such advancements are also applicable to the next generation fluorophores and imaging agents currently emerging from clinical trials. In addition, by providing an understandable, applicable method for detailed tissue characterisation visually, such technology paves the way for acceptance of other AI methodology during surgery including, potentially, deep learning methods based on whole screen/video detailing.

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiation of soft tissue sarcoma from benign lesions: a systematic review of literature

OBJECTIVE

To systematically review the literature assessing the role of Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) in the differentiation of soft tissue sarcomas from benign lesions.

MATERIALS AND METHODS

A comprehensive literature search was performed with the following keywords: multiparametric magnetic resonance imaging, DCE-MR perfusion, soft tissue, sarcoma, and neoplasm. Original studies evaluating the role of DCE-MRI for differentiating benign soft-tissue lesions from soft-tissue sarcomas were included.

RESULTS

Eighteen studies with a total of 965 imaging examinations were identified. Ten of twelve studies evaluating qualitative parameters reported improvement in discriminative power. One of the evaluated qualitative parameters was time-intensity curves (TIC), and malignant curves (TIC III, IV) were found in 74% of sarcomas versus 26.5% benign lesions. Six of seven studies that used the semiquantitative approach found it relatively beneficial. Four studies assessed quantitative parameters including Ktrans (contrast transit from the vascular compartment to the interstitial compartment), Kep (contrast return to the vascular compartment), and Ve (the volume fraction of the extracellular extravascular space) in addition to other parameters. All found Ktrans, and 3 studies found Kep to be significantly different between sarcomas and benign lesions. The values for Ve were variable. Additionally, eight studies assessed diffusion-weighted imaging (DWI), and 6 of them found it useful.

CONCLUSION

Of different DCE-MRI approaches, qualitative parameters showed the best evidence in increasing the diagnostic performance of MRI. Semiquantitative and quantitative approaches seemed to improve the discriminative power of MRI, but which parameters and to what extent is still unclear and needs further investigation.

Deep Learning-Based Multiparametric MRI Model for Preoperative T-Stage in Rectal Cancer

BACKGROUND

Conventional MRI staging can be challenging in the preoperative assessment of rectal cancer. Deep learning methods based on MRI have shown promise in cancer diagnosis and prognostication. However, the value of deep learning in rectal cancer T-staging is unclear.

PURPOSE

To develop a deep learning model based on preoperative multiparametric MRI for evaluation of rectal cancer and to investigate its potential to improve T-staging accuracy.

STUDY TYPE

Retrospective.

POPULATION

After cross-validation, 260 patients (123 with T-stage T1-2 and 134 with T-stage T3-4) with histopathologically confirmed rectal cancer were randomly divided to the training (N = 208) and test sets (N = 52).

FIELD STRENGTH/SEQUENCE

3.0 T/Dynamic contrast enhanced (DCE), T2-weighted imaging (T2W), and diffusion-weighted imaging (DWI).

ASSESSMENT

The deep learning (DL) model of multiparametric (DCE, T2W, and DWI) convolutional neural network were constructed for evaluating preoperative diagnosis. The pathological findings served as the reference standard for T-stage. For comparison, the single parameter DL-model, a logistic regression model composed of clinical features and subjective assessment of radiologists were used.

STATISTICAL TESTS

The receiver operating characteristic curve (ROC) was used to evaluate the models, the Fleiss' kappa for the intercorrelation coefficients, and DeLong test for compare the diagnostic performance of ROCs. P-values less than 0.05 were considered statistically significant.

RESULTS

The Area Under Curve (AUC) of the multiparametric DL-model was 0.854, which was significantly higher than the radiologist's assessment (AUC = 0.678), clinical model (AUC = 0.747), and the single parameter DL-models including T2W-model (AUC = 0.735), DWI-model (AUC = 0.759), and DCE-model (AUC = 0.789).

DATA CONCLUSION

In the evaluation of rectal cancer patients, the proposed multiparametric DL-model outperformed the radiologist's assessment, the clinical model as well as the single parameter models. The multiparametric DL-model has the potential to assist clinicians by providing more reliable and precise preoperative T staging diagnosis.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Dynamic contrast-enhanced magnetic resonance imaging parameter changes as an early biomarker of tumor responses following radiation therapy in patients with spinal metastases: a systematic review

PURPOSE

This systematic review aims to assess and summarize the clinical values of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameter changes as early biomarkers of tumor responses following radiation therapy (RT) in patients with spinal metastases.

MATERIALS AND METHODS

A systematic search was conducted on five electronic databases: PubMed, Scopus, Science Direct, Cochrane, and Embase. Studies were included if they mentioned DCE-MRI parameter changes before and after RT in patients with spinal metastases with a correlation to tumor responses based on clinical and imaging criteria. The Quality Assessment of Diagnostic Accuracy Studies 2 was used to assess study quality.

RESULTS

This systematic review included seven studies involving 107 patients. All seven studies evaluated the transfer constant (Ktrans), six studies evaluated the plasma volume fraction (Vp), three studies evaluated the extravascular extracellular space volume fraction, and two studies evaluated the rate constant. There were variations in the type of primary cancer, RT techniques used, post-treatment scan time, and median follow-up time. Despite the variations, however, the collected evidence generally suggested that significant differences could be detected in DCE-MRI parameters between before and after RT, which might reflect treatment success or failures in long-term follow-up. Responders showed higher reduction and lower values of Ktrans and Vp after RT. DCE-MRI parameters showed changes and detectable recurrences significantly earlier (up to 6 months) than conventional MRI with favorable diagnostic values.

CONCLUSION

The results of this systematic review suggested that DCE-MRI parameter changes in patients with spinal metastases could be a promising tool for treatment-response assessment following RT. Lower values and higher reduction of Ktrans and Vp after treatment demonstrated good prediction of local control. Compared to conventional MRI, DCE-MRI showed more rapid changes and earlier prediction of treatment failure.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

CLINICAL RELEVANCE STATEMENT

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

KEY POINTS

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

Dynamic Contrast-Enhanced Study in the mpMRI of the Prostate-Unnecessary or Underutilised? A Narrative Review

The aim of this review is to summarise recent scientific literature regarding the clinical use of DCE-MRI as a component of multiparametric resonance imaging of the prostate. This review presents the principles of DCE-MRI acquisition and analysis, the current role of DCE-MRI in clinical practice with special regard to its role in presently available categorisation systems, and an overview of the advantages and disadvantages of DCE-MRI described in the current literature. DCE-MRI is an important functional sequence that requires intravenous administration of a gadolinium-based contrast agent and gives information regarding the vascularity and capillary permeability of the lesion. Although numerous studies have confirmed that DCE-MRI has great potential in the diagnosis and monitoring of prostate cancer, its role is still inadequate in the PI-RADS categorisation. Moreover, there have been numerous scientific discussions about abandoning the intravenous application of gadolinium-based contrast as a routine part of MRI examination of the prostate. In this review, we summarised the recent literature on the advantages and disadvantages of DCE-MRI, focusing on an overview of currently available data on bpMRI and mpMRI, as well as on studies providing information on the potential better usability of DCE-MRI in improving the sensitivity and specificity of mpMRI examinations of the prostate.

Predicting response to chemoradiotherapy in rectal cancer via visual morphologic assessment and staging on baseline MRI: a multicenter and multireader study

PURPOSE

Pre-treatment knowledge of the anticipated response of rectal tumors to neoadjuvant chemoradiotherapy (CRT) could help to further optimize the treatment. Van Griethuysen et al. proposed a visual 5-point confidence score to predict the likelihood of response on baseline MRI. Aim was to evaluate this score in a multicenter and multireader study setting and compare it to two simplified (4-point and 2-point) adaptations in terms of diagnostic performance, interobserver agreement (IOA), and reader preference.

METHODS

Twenty-two radiologists from 14 countries (5 MRI-experts,17 general/abdominal radiologists) retrospectively reviewed 90 baseline MRIs to estimate if patients would likely achieve a (near-)complete response (nCR); first using the 5-point score by van Griethuysen (1=highly unlikely to 5=highly likely to achieve nCR), second using a 4-point adaptation (with 1-point each for high-risk T-stage, obvious mesorectal fascia invasion, nodal involvement, and extramural vascular invasion), and third using a 2-point score (unlikely/likely to achieve nCR). Diagnostic performance was calculated using ROC curves and IOA using Krippendorf's alpha (α).

RESULTS

Areas under the ROC curve to predict the likelihood of a nCR were similar for the three methods (0.71-0.74). IOA was higher for the 5- and 4-point scores (α=0.55 and 0.57 versus 0.46 for the 2-point score) with best results for the MRI-experts (α=0.64-0.65). Most readers (55%) favored the 4-point score.

CONCLUSIONS

Visual morphologic assessment and staging methods can predict neoadjuvant treatment response with moderate-good performance. Compared to a previously published confidence-based scoring system, study readers preferred a simplified 4-point risk score based on high-risk T-stage, MRF involvement, nodal involvement, and EMVI.

Quantitative dynamic contrast-enhance MRI parameters for rectal carcinoma characterization: correlation with tumor tissue composition

OBJECTIVE

To investigate the relationship between dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) measurements and the potential composition of rectal carcinoma.

METHODS

Twenty-four patients provided informed consent for this study. DCE-MRI was performed before total mesorectal excision. Quantitative parameters were calculated based on a modified Tofts model. Whole-mount immunohistochemistry and Masson staining sections were generated and digitized at histological resolution. The percentage of tissue components area was measured. Pearson correlation analysis was used to evaluate the correlations between pathological parameters and DCE-MRI parameters.

RESULTS

On the World Health Organization (WHO) grading scale, there were significant differences in extracellular extravascular space (Ktrans) (F = 9.890, P = 0.001), mean transit time (MTT) (F = 9.890, P = 0.038), CDX-2 (F = 4.935, P = 0.018), and Ki-67 (F = 4.131, P = 0.031) among G1, G2, and G3. ECV showed significant differences in extramural venous invasion (t =  - 2.113, P = 0.046). Ktrans was strongly positively correlated with CD34 (r = 0.708, P = 0.000) and moderately positively correlated with vimentin (r = 0.450, P = 0.027). Interstitial volume (Ve) was moderately positively correlated with Masson's (r = 0.548, P = 0.006) and vimentin (r = 0.417, P = 0.043). There was a moderate negative correlation between Ve and CDX-2 (r =  - 0.441, P = 0.031). The rate constant from extracellular extravascular space to blood plasma (Kep) showed a strong positive correlation with CD34 expression (r = 0.622, P = 0.001). ECV showed a moderate negative correlation with CDX-2 (r =  - 0.472, P = 0.020) and a moderate positive correlation with collagen fibers (r = 0.558, P = 0.005).

CONCLUSION

The dynamic contrast-enhanced MRI-derived parameters measured in rectal cancer were significantly correlated with the proportion of histological components. This may serve as an optimal imaging biomarker to identify tumor tissue components.

Shear wave elastography can stratify rectal cancer response to short-course radiation therapy

Rectal cancer is a deadly disease typically treated using neoadjuvant chemoradiotherapy followed by total mesorectal excision surgery. To reduce the occurrence of mesorectal excision surgery for patients whose tumors regress from the neoadjuvant therapy alone, conventional imaging, such as computed tomography (CT) or magnetic resonance imaging (MRI), is used to assess tumor response to neoadjuvant therapy before surgery. In this work, we hypothesize that shear wave elastography offers valuable insights into tumor response to short-course radiation therapy (SCRT)-information that could help distinguish radiation-responsive from radiation-non-responsive tumors and shed light on changes in the tumor microenvironment that may affect radiation response. To test this hypothesis, we performed elastographic imaging on murine rectal tumors (n = 32) on days 6, 10, 12, 16, 18, 20, 23, and 25 post-tumor cell injection. The study revealed that radiation-responsive and non-radiation-responsive tumors had different mechanical properties. Specifically, radiation-non-responsive tumors showed significantly higher shear wave speed SWS (p < 0.01) than radiation-responsive tumors 11 days after SCRT. Furthermore, there was a significant difference in shear wave attenuation (SWA) (p < 0.01) in radiation-non-responsive tumors 16 days after SCRT compared to SWA measured just one day after SCRT. These results demonstrate the potential of shear wave elastography to provide valuable insights into tumor response to SCRT and aid in exploring the underlying biology that drives tumors' responses to radiation.

Is Nonoperative Management of Rectal Cancer Feasible?

During the past decade, the treatment of locally advanced rectal cancer (LARC) has become more complex. Total neoadjuvant treatment (TNT) has increased the rates of both clinical and pathologic complete response, resulting in improved long-term oncological outcomes. The feasibility to implement nonoperative management (NOM) depends on solving current challenges such as how to correctly identify the best candidates for a NOM without compromising oncologic safety. NOM should be part of the treatment discussion of LARC, considering increasing rates of clinical complete response, potential quality of life gains, avoidance of surgical morbidity, and patient preferences.

Distinguishing mesorectal tumor deposits from metastatic lymph nodes by using diffusion-weighted and dynamic contrast-enhanced magnetic resonance imaging in rectal cancer

OBJECTIVES

This study aimed to identify whether apparent diffusion coefficient (ADC) values and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters are helpful in distinguishing mesorectal tumor deposits (TD) from metastatic lymph nodes (MLN) in rectal cancer (RC).

METHODS

Thirty patients (59 lesions, including 30 TD and 29 MLN) with RC who underwent pretreatment-MRI between February 2016 and August 2018 were enrolled. The morphological features, ADC values, and semi-quantitative parameters of DCE-MRI, including relative enhancement (RE), maximum enhancement (ME), maximum relative enhancement (MRE), time to peak (TTP), wash-in rates (WIR), wash-out rates (WOR), brevity of enhancement (BRE), and area under the curve (AUC) were measured on lesions (TD or MLN) and RC. The parameters were compared between TD and MLN, tumor with and without TD group by using Fisher's exact test, independent-samples t-test, and Mann-Whitney U test. The ratio (lesion-to-tumor) of the parameters was compared between TD and MLN. Receiver operating characteristic curve analysis and binary logistic regression analysis were used to assess the diagnostic ability of single and combined metrics for distinguishing TD from MLN.

RESULTS

The morphological features, including size, shape, and border, were significantly different between TD and MLN. TD exhibited significantly lower RE, MRE, RE-ratio, MRE-ratio, ADC_min-ratio, and ADC_mean-ratio than MLN. RE-ratio showed the highest AUC (0.749) and accuracy (77.97%) among single parameters. The combination of DCE-MRI and DWI parameters together showed higher diagnostic efficiency (AUC = 0.825).

CONCLUSIONS

Morphological features, ADC values, and DCE-MRI parameters can preoperatively help distinguish TD from MLN in RC.

KEY POINTS

• DWI and DCE-MRI can facilitate early detection and distinguishing mesorectal TD (tumor deposits) from MLN (metastatic lymph nodes) in rectal cancer preoperatively. • TD has some specific morphological features, including relatively larger size, lower short- to long-axis ratio, irregular shape, and ill-defined border on T2-weighted MR images in rectal cancer. • The combination of ADC values and semi-quantitative parameters of DCE-MRI (RE, MRE) can help to improve the diagnostic efficiency of TD in rectal cancer.

Value of texture analysis based on dynamic contrast-enhanced magnetic resonance imaging in preoperative assessment of extramural venous invasion in rectal cancer

Objective

Accurate preoperative assessment of extramural vascular invasion (EMVI) is critical for the treatment and prognosis of rectal cancer. The aim of our research was to develop an assessment model by texture analysis for preoperative prediction of EMVI.

Materials and methods

This study enrolled 44 rectal patients as train cohort, 7 patients as validation cohort and 18 patients as test cohort. A total of 236 texture features from DCE MR imaging quantitative parameters were extracted for each patient (59 features of Ktrans, Kep, Ve and Vp), and key features were selected by least absolute shrinkage and selection operator regression (LASSO). Finally, clinical independent risk factors, conventional MRI assessment, and T-score were incorporated to construct an assessment model using multivariable logistic regression.

Results

The T-score calculated using the 4 selected key features were significantly correlated with EMVI (p < 0.010). The area under the receiver operating characteristic curve (AUC) was 0.797 for discriminating between EMVI-positive and EMVI-negative patients with a sensitivity of 88.2% and specificity of 70.4%. The conventional MRI assessment of EMVI had a sensitivity of 23.53% and a specificity of 96.30%. The assessment model showed a greatly improved performance with an AUC of 0.954 (sensitivity, 88.2%; specificity, 92.6%) in train cohort, 0.833 (sensitivity, 66.7%; specificity, 100%) in validation cohort and 0.877 in test cohort, respectively.

Conclusions

The assessment model showed an excellent performance in preoperative assessment of EMVI. It demonstrates strong potential for improving the accuracy of EMVI assessment and provide a reliable basis for individualized treatment decisions.

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.

Predictive value of DCE-MRI and IVIM-DWI in osteosarcoma patients with neoadjuvant chemotherapy

Objective

To investigate the predictive value of dynamic contrast enhanced MRI (DCE-MRI) and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for clinical outcomes of osteosarcoma patients with neoadjuvant chemotherapy.

Methods

The present prospective single-arm cohort study enrolled 163 patients of osteosarcoma during July 2017 to July 2022. All patients received the same treatment strategy of neoadjuvant chemotherapy. Both DCE-MRI and IVIM-DWI were conducted for the patients before the chemotherapy, as well as after one or two chemotherapy treatment cycles. The imaging parameters of contrast agent transfer rate between blood and tissue (K^trans), contrast agent back-flux rate constant (K_ep), extravascular extracellular fractional volume (V_e), as well as pure diffusion coefficient (D value), pseudo-diffusion coefficient (D* value), apparent diffusion coefficient (ADC) and the perfusion fraction (f value) were recorded. RECIST standard [complete response (CR), partial response (PR), stable disease (SD), progressive disease (PD)] was used as the main clinical outcome.

Results

After two treatment cycles, 112 (68.71%) cases were with CR and PR, 31 (19.02%) cases were with SD and 20 cases (12.27%) were with PD. After 1~2 treatment cycles, patients with CR/PR showed significantly markedly lower K^trans, K_ep, V_e values, while higher D, ADC and f values compared with SD or PD patients. Alkaline phosphatase (ALP) and lactate dehydrogenase (LDH) were positively correlated with values of K^trans, K_ep, and V_e, while negative correlation was observed between ALP and values of D, ADC and f, as well as between LDH and D and ADC after the whole treatment. D and K_ep values after two treatment cycles showed the best predictive value for diagnosis of PD. The values of K^tran, K_ep, ADC as well as ALP and LDH were all risk factors for PD after neoadjuvant chemotherapy.

Conclusion

DCE-MRI and IVIM-DWI have the potential to predict clinical outcomes of osteosarcoma patients with neoadjuvant chemotherapy.

Non-Operative Management of Patients with Rectal Cancer: Lessons Learnt from the OPRA Trial

Over the past decade, the management of locally advanced rectal cancer (LARC) has progressively become more complex. The introduction of total neoadjuvant treatment (TNT) has increased the rates of both clinical and pathological complete response, resulting in excellent long-term oncological outcomes. As a result, non-operative management (NOM) of LARC patients with a clinical complete response (cCR) after neoadjuvant therapy has gained acceptance as a potential treatment option in selected cases. NOM is based on replacement of surgical resection with safe and active surveillance. However, the identification of appropriate candidates for a NOM strategy without compromising oncologic safety is currently challenging due to the lack of an objective standardization. NOM should be part of the treatment plan discussion with LARC patients, considering the increasing rates of cCR, patient preference, quality of life, expectations, and the potential avoidance of surgical morbidity. The recently published OPRA trial showed that organ preservation is achievable in half of rectal cancer patients treated with TNT, and that chemoradiotherapy followed by consolidation chemotherapy may an appropriate strategy to maximize cCR rates. Ongoing trials are investigating optimal algorithms of TNT delivery to further expand the pool of patients who may benefit from NOM of LARC.

Nonoperative Management for Rectal Cancer

The treatment algorithm for locally advanced rectal cancer (LARC) has increased in complexity over the past 10 years. Nonoperative management (NOM) for rectal cancer in patients with clinical complete response (cCR) after neoadjuvant therapy has been gaining acceptance as a potential treatment option for selected LARC patients. The current challenge is to accurately select the patients with an apparent cCR, thereby correctly identifying those would-be appropriate candidates for a NOM strategy. NOM should be part of the treatment discussion of LARC, considering increasing rates of cCR, patient preference, potential quality of life gains, and the potential avoidance of surgical morbidity.

Preoperative prediction of extramural venous invasion in rectal cancer by dynamic contrast-enhanced and diffusion weighted MRI: a preliminary study

Background

To explore the value of the quantitative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) parameters in assessing preoperative extramural venous invasion (EMVI) in rectal cancer.

Methods

Eighty-two rectal adenocarcinoma patients who had underwent MRI preoperatively were enrolled in this study. The differences in quantitative DCE-MRI and DWI parameters including Krans, Kep and ADC values were analyzed between MR-detected EMVI (mrEMVI)-positive and -negative groups. Multivariate logistic regression analysis was performed to build the combined prediction model for pathologic EMVI (pEMVI) with statistically significant quantitative parameters. The performance of the model for predicting pEMVI was evaluated using receiver operating characteristic (ROC) curve.

Results

Of the 82 patients, 24 were mrEMVI-positive and 58 were -negative. In the mrEMVI positive group, the Ktrans and Kep values were significantly higher than those in the mrEMVI negative group (P < 0.01), but the ADC values were significantly lower (P < 0.01). A negative correlation was observed between the Ktrans vs ADC values and Kep vs ADC values in patients with rectal cancer. Among the four quantitative parameters, Ktrans and ADC value were independently associated with mrEMVI by multivariate logistic regression analysis. ROC analysis showed that combined prediction model based on quantitative DCE parameters and ADC values had a good prediction efficiency for pEMVI in rectal cancer.

Conclusion

The quantitative DCE-MRI parameters, Krans, Kep and ADC values play important role in predicting EMVI of rectal cancer, with Ktrans and ADC value being independent predictors of EMVI in rectal cancer.

Semi-automatic tumor segmentation of rectal cancer based on functional magnetic resonance imaging

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Machine learning on magnetic resonance images (MRI) was used for tumor segmentation.

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Voxelwise machine learning with morphological post-processing achieved good segmentation results.

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Combining T2-weighted with functional MRI improved semi-automatic tumor segmentation.

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Dynamic contrast enhanced MRI was the most valuable functional MRI information.

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Tumor volume and interobserver variation were linked to measured segmentation quality.

Background and purpose

Tumor delineation is required both for radiotherapy planning and quantitative imaging biomarker purposes. It is a manual, time- and labor-intensive process prone to inter- and intraobserver variations. Semi or fully automatic segmentation could provide better efficiency and consistency. This study aimed to investigate the influence of including and combining functional with anatomical magnetic resonance imaging (MRI) sequences on the quality of automatic segmentations.

Materials and methods

T2-weighted (T2w), diffusion weighted, multi-echo T2*-weighted, and contrast enhanced dynamic multi-echo (DME) MR images of eighty-one patients with rectal cancer were used in the analysis. Four classical machine learning algorithms; adaptive boosting (ADA), linear and quadratic discriminant analysis and support vector machines, were trained for automatic segmentation of tumor and normal tissue using different combinations of the MR images as input, followed by semi-automatic morphological post-processing. Manual delineations from two experts served as ground truth. The Sørensen-Dice similarity coefficient (DICE) and mean symmetric surface distance (MSD) were used as performance metric in leave-one-out cross validation.

Results

Using T2w images alone, ADA outperformed the other algorithms, yielding a median per patient DICE of 0.67 and MSD of 3.6 mm. The performance improved when functional images were added and was highest for models based on either T2w and DME images (DICE: 0.72, MSD: 2.7 mm) or all four MRI sequences (DICE: 0.72, MSD: 2.5 mm).

Conclusion

Machine learning models using functional MRI, in particular DME, have the potential to improve automatic segmentation of rectal cancer relative to models using T2w MRI alone.

Multi-parameter diffusion and perfusion magnetic resonance imaging and radiomics nomogram for preoperative evaluation of aquaporin-1 expression in rectal cancer

PURPOSE

The overexpression of aquaporin-1 (AQP1) is associated with poor prognosis in rectal cancer. This study aimed to explore the value of multi-parameter diffusion and perfusion MRI and radiomics models in predicting AQP1 high expression.

METHODS

This prospective study was performed from July 2019 to February 2021, which included rectal cancer participants after preoperative rectal MRI, with diffusion-weighted imaging, intravoxel incoherent motion (IVIM), diffusion kurtosis imaging (DKI), and dynamic contrast-enhanced (DCE) sequences. Radiomic features were extracted from MR images, and immunohistochemical tests assessed AQP1 expression. Selected quantitative MRI and radiomic features were analyzed. Receiver operating characteristic (ROC) curves evaluated the predictive performance. The nomogram performance was evaluated by its calibration, discrimen, and clinical utility. The intraclass correlation coefficient evaluated the interobserver agreement for the MRI features.

RESULTS

110 participants with the age of 60.7 ± 12.5 years been enrolled in this study. The apparent diffusion coefficient (ADC), IVIM_D, DKI_diffusivity, and DCE_Ktrans were significantly higher in participants with high AQP1 expression than in those with low expression (P < 0.05). ADC (b = 1000, 2000, and 3000 s/mm²), IVIM_D, DKI_diffusivity, and DCE_Ktrans were positively correlated (r = 0.205, 0.275, 0.37, 0.235, 0.229, and 0.227, respectively; P < 0.05), whereas DKI_Kurtosis was negatively correlated (r = - 0.22, P = 0.021) with AQP1 expression. ADC (b = 3000 s/mm²), IVIM_D, DKI_ diffusivity, DKI_Kurtosis, and DCE_Ktrans had moderate diagnostic efficiencies for high AQP1 expression (AUC = 0.715, 0.636, 0.627, 0.633, and 0.632, respectively; P < 0.05). The radiomic features had excellent predictive efficiency for high AQP1 expression (AUC = 0.967 and 0.917 for training and validation). The model-based nomogram had C-indexes of 0.932 and 0.851 for the training and validation cohorts, which indicated good fitting to the calibration curves (p > 0.05).

CONCLUSION

Diffusion and perfusion MRI can indicate the aquaporin-1 expression in rectal cancer, and radiomic features can enhance the predictive efficiency for high AQP1 expression. A nomogram for high aquaporin-1 expression will improve clinical decision-making.

The importance of MRI for rectal cancer evaluation

Magnetic resonance imaging (MRI) has gained increasing importance in the management of rectal cancer over the last two decades. The role of MRI in patients with rectal cancer has expanded beyond the tumor-node-metastasis (TNM) system in both staging and restaging scenarios and has contributed to identifying "high" and "low" risk features that can be used to tailor and personalize patient treatment; for instance, selecting the patients for neoadjuvant chemoradiation (NCRT) before the total mesorectal excision (TME) surgery based on risk of recurrence. Among those features, the status of the circumferential resection margin (CRM), extramural vascular invasion (EMVI), and tumor deposits (TD) have stood out. Moreover, MRI also has played a role in surgical planning, especially when the tumor is located in the low rectum, when the relationship between tumor and the anal canal is important to choose the best surgical approach, and in cases of locally advanced or recurrent tumors invading adjacent pelvic organs that may require more complex surgeries such as pelvic exenteration. As approaches using organ preservation emerge, including transanal local excision and "watch-and-wait", MRI may help in the patient selection for those treatments, follow up, and detection of tumor regrowth. Additionally, potential MRI-based prognostic and predictive biomarkers, such as quantitative and semi-quantitative metrics derived from functional sequences like diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE), and radiomics, are under investigation. This review provides an overview of the current role of MRI in rectal cancer in staging and restaging and highlights the main areas under investigation and future perspectives.

Low-Rank Matrix Denoising Algorithm-Based MRI Image Feature for Therapeutic Effect Evaluation of NCRT on Rectal Cancer

This study aimed to explore the therapeutic effects of neoadjuvant chemoradiotherapy (NCRT) on rectal cancer patients using the MRI based on low-rank matrix denoising algorithm, which was then compared with the postoperative pathological examination to evaluate its application value in tumor staging after NCRT treatment. 15 patients with rectal cancer who met the requirements of radiotherapy and chemotherapy after conventional MRI were selected as the research subjects. The conventional MRI images before and after NCRT treatment were divided in two groups. One group was not processed and set as the conventional group; the other group was processed with low-rank matrix denoising algorithm and set as the optimized group. The two groups of images were observed for the changes in the ADC value and length and thickness of the tumor before and after NCRT treatment. The two groups were compared with the pathological examination for the complete remission of pathology (pCR) after the NCRT treatment and the tumor stage results. The results showed that Root Mean Square Error (RMSE) and Peak Signal to Noise Ratio (PSNR) (18.9121 and 74.9911 dB) after introducing the low-rank matrix denoising algorithm were significantly better than those before (20.1234 and 70.1234 dB) (P < 0.05); there were notable differences in the tumor index data within the two groups before and after NCRT treatment (P < 0.05), indicating that the NCRT treatment was effective. The pathological examination results of pCR data of the two groups were not much different (P > 0.05); the examination results between the two groups were different, but no notable difference was noted (P < 0.05); in the optimized group, there was no notable difference between the MRI results and the pathological examination results (P < 0.05), while in the conventional group, there were notable differences in the MRI results and pathological examination results (P < 0.05). In conclusion, MRI images based on low-rank matrix denoising algorithm are clearer, which can improve the diagnosis rate of patients and better display the changes of the microenvironment after NCRT treatment. It also indicates that NCRT treatment has significant clinical effects in the treatment of rectal cancer patients, which is worth promoting.

Current State of Neoadjuvant Radiotherapy for Rectal Cancer

Colorectal cancer is the third most commonly diagnosed cancer, with rectal cancer accounting for 30% of cases. The current standard of care curative treatment for locally advanced rectal cancer is (chemo)radiotherapy followed by surgery and adjuvant chemotherapy. Although neoadjuvant radiotherapy has reduced the risk of local recurrence to less than 10%, the risk of distant metastasis remained high at 30% affecting patient survival. In addition, there is a recognition that there is heterogeneity in tumor biology and treatment response with good responders potentially suitable for treatment de-escalation. Therefore, new treatment sequencing and regimens were investigated. Here, we reviewed the evidence for current neoadjuvant treatment options in patients with locally advanced rectal adenocarcinoma, and highlight the new challenges in this new treatment landscape.

Radiomics modelling in rectal cancer to predict disease-free survival: evaluation of different approaches

BACKGROUND

Radiomics may be useful in rectal cancer management. The aim of this study was to assess and compare different radiomics approaches over qualitative evaluation to predict disease-free survival (DFS) in patients with locally advanced rectal cancer treated with neoadjuvant therapy.

METHODS

Patients from a phase II, multicentre, randomized study (GRECCAR4; NCT01333709) were included retrospectively as a training set. An independent cohort of patients comprised the independent test set. For both time points and both sets, radiomic features were extracted from two-dimensional manual segmentation (MS), three-dimensional (3D) MS, and from bounding boxes. Radiomics predictive models of DFS were built using a hyperparameters-tuned random forests classifier. Additionally, radiomics models were compared with qualitative parameters, including sphincter invasion, extramural vascular invasion as determined by MRI (mrEMVI) at baseline, and tumour regression grade evaluated by MRI (mrTRG) after chemoradiotherapy (CRT).

RESULTS

In the training cohort of 98 patients, all three models showed good performance with mean(s.d.) area under the curve (AUC) values ranging from 0.77(0.09) to 0.89(0.09) for prediction of DFS. The 3D radiomics model outperformed qualitative analysis based on mrEMVI and sphincter invasion at baseline (P = 0.038 and P = 0.027 respectively), and mrTRG after CRT (P = 0.017). In the independent test cohort of 48 patients, at baseline and after CRT the AUC ranged from 0.67(0.09) to 0.76(0.06). All three models showed no difference compared with qualitative analysis in the independent set.

CONCLUSION

Radiomics models can predict DFS in patients with locally advanced rectal cancer.

Comparison of Diagnostic Performance between Perfusion-Related Intravoxel Incoherent Motion DWI and Dynamic Contrast-Enhanced MRI in Rectal Cancer

This study was aimed to determine the diagnostic performance of perfusion-related parameters derived from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) by comparing them with quantitative parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based on differentiation grades of rectal cancer. We retrospectively analyzed 98 patients with rectal cancer. Perfusion-related IVIM parameters (D^∗, f, and f·D^∗) and quantitative DCE parameters (K^trans, K_ep, V_e, and V_p) were obtained by plotting the volume-of-interest on in-house software. Furthermore, we compared the difference and diagnostic performance of all well-moderately and poorly differentiated rectal cancer parameters. Finally, we analyzed the correlation between those DCE and IVIM parameters and pathological differentiation grade. The values of f, K^trans, and K_ep significantly differentiated poor and well-moderate rectal cancers. K^trans achieved the highest area under the curve (AUC) value compared to perfusion-related IVIM and DCE parameters. Furthermore, K^trans showed a better correlation with pathological differentiation grade than f. The diagnostic efficiency of DCE-MRI was greater than perfusion-related IVIM parameters. The f value derived from perfusion-related IVIM offered a diagnostic performance similar to DCE-MRI for patients with renal insufficiency.

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

Objective

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

Methods

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

Results

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

Conclusion

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

Diagnostic Performance of Vascular Permeability and Texture Parameters for Evaluating the Response to Neoadjuvant Chemoradiotherapy in Patients With Esophageal Squamous Cell Carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is an aggressive type of cancer, associated with poor prognosis. The development of an accurate and non-invasive method to evaluate the pathologic response of patients with ESCC to chemoradiotherapy remains a critical issue. Therefore, the aim of this study was to assess the importance of vascular permeability and texture parameters in predicting the response to neoadjuvant chemoradiotherapy (NACRT) in patients with ESCC.

Methods

This prospective analysis included patients with T1–T2 stage of ESCC, without either lymphatic or metastasis, and distant metastasis. All patients underwent surgery having received two rounds of NACRT. All patients underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) twice, i.e., before the first NACRT and after the second NACRT. Patients were assessed for treatment response at 30 days after the second NACRT. Patients were divided into the complete response (CR) and partial response (PR) groups based on their responses to NACRT. Vascular permeability and texture parameters were extracted from the DCE-MRI scans. After assessing the diagnostic performance of individual parameters, a combined model with vascular permeability and texture parameters was generated to predict the response to NACRT.

Results

In this study, the CR and PR groups included 16 patients each. The volume transfer constant (Ktrans), extracellular extravascular volume fraction (ve), and entropy values, as well as changes to each of these parameters, extracted from the second DCE-MRI scans, showed significant differences between the CR and PR groups. The area under the curve (AUC) of Ktrans, ve, and entropy values showed good diagnostic ability (0.813, 0.789, and 0.707, respectively). A logistic regression model combining Ktrans, ve, and entropy had significant diagnostic ability (AUC=0.977).

Conclusions

The use of a combined model with vascular permeability and texture parameters can improve post-NACRT prognostication in patients with ESCC.

Endoscopic and MRI response evaluation following neoadjuvant treatment for rectal cancer: a pictorial review with matched MRI, endoscopic, and pathologic examples

A nonoperative management strategy, or Watch-and-Wait, following neoadjuvant therapies of locally advanced rectal adenocarcinoma is increasingly considered for select patients. Yet, standardized tumor response assessment to best select and surveil suitable patients remains an unmet clinical challenge. Endoscopic and MRI currently provide the most reliable tumor response estimations. However, resources illustrating variable tumor responses to neoadjuvant therapies remain limited. This pictorial review aims to provide detailed and annotated examples of common endoscopic and MRI findings of rectal cancer treatment response, while also emphasizing their respective diagnostic shortcomings and consequently, the necessity for a multidisciplinary approach to optimally manage these patients.

Multi-parametric magnetic resonance imaging assessment of whole tumour heterogeneity for chemoradiotherapy response prediction in rectal cancer

Background and purpose

Prediction of chemoradiotherapy response (CRT) in locally advanced rectal cancer would enable stratification of management. The purpose was to prospectively evaluate multi-parametric magnetic resonance imaging (MRI) assessment of tumour heterogeneity combining diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE) MRI for the prediction of CRT response in locally advanced rectal cancer.

Materials and methods

Patients with Stage II or III rectal adenocarcinoma undergoing neoadjuvant CRT and surgery underwent MRI (DWI and DCE) before, during (week 3), and after CRT (1 week before surgery). Patients with histopathology tumour regression grade (TRG) 0-1 were classified as responders, and TRG 2-3 were classified as non-responders. A whole tumour voxel-wise technique was used to produce apparent diffusion coefficient (ADC) and K^trans (Tofts model) histograms derived from DWI and DCE-MRI, respectively. Logistic regression was used to predict response status for ADC and K^trans quantiles.

Results

Thirty-three patients were included in this analysis; 16 responders, and 17 non-responders. On heterogeneity analysis, odds of being a responder were significantly higher after CRT (before surgery) for higher ADC 75th (p = 0.049) and ADC 90th (p = 0.034) percentile values. The K^trans quantiles were lower in non-responders than responders before and during CRT, and higher after CRT although no significant association with response status was observed (p ≥ 0.10).

Conclusions

DWI-MRI after CRT (before surgery) incorporating a histogram analysis of whole tumour heterogeneity was predictive of CRT response in patients with locally advanced rectal cancer. DCE-MRI did not add value in response prediction.

Clinical trial registration

Australian New Zealand Clinical Trials Registry (ANZCTR) number ACTRN12616001690448.

An MRI-Based Radiomic Prognostic Index Predicts Poor Outcome and Specific Genetic Alterations in Endometrial Cancer

Integrative tumor characterization linking radiomic profiles to corresponding gene expression profiles has the potential to identify specific genetic alterations based on non-invasive radiomic profiling in cancer. The aim of this study was to develop and validate a radiomic prognostic index (RPI) based on preoperative magnetic resonance imaging (MRI) and assess possible associations between the RPI and gene expression profiles in endometrial cancer patients. Tumor texture features were extracted from preoperative 2D MRI in 177 endometrial cancer patients. The RPI was developed using least absolute shrinkage and selection operator (LASSO) Cox regression in a study cohort (n = 95) and validated in an MRI validation cohort (n = 82). Transcriptional alterations associated with the RPI were investigated in the study cohort. Potential prognostic markers were further explored for validation in an mRNA validation cohort (n = 161). The RPI included four tumor texture features, and a high RPI was significantly associated with poor disease-specific survival in both the study cohort (p < 0.001) and the MRI validation cohort (p = 0.030). The association between RPI and gene expression profiles revealed 46 significantly differentially expressed genes in patients with a high RPI versus a low RPI (p < 0.001). The most differentially expressed genes, COMP and DMBT1, were significantly associated with disease-specific survival in both the study cohort and the mRNA validation cohort. In conclusion, a high RPI score predicts poor outcome and is associated with specific gene expression profiles in endometrial cancer patients. The promising link between radiomic tumor profiles and molecular alterations may aid in developing refined prognostication and targeted treatment strategies in endometrial cancer.

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

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

Lateral pelvic lymph node dissection in the management of locally advanced low rectal cancer: Summary of the current evidence

Lateral pelvic lymph nodes (LPLN) are a major site for local recurrence following curative resection for low locally advanced rectal cancer. Ongoing advances in imaging techniques have improved predicting LPLN metastasis (LPLNM) during pre-operative staging. However, there is ongoing debate on optimal management of this subgroup of patients with variation between guidance of different societies. In Japan, LPLNM is considered as local disease and addressed by lateral pelvic node dissection (LPLND) in addition to total mesorectal excision (TME). However, in the west, LPLNM is considered as metastatic disease and those patients are offered neoadjuvant chemoradiotherapy (nCRT) followed by TME surgery. The potential surgical risks and morbidity associated with LPLND as well as the uncertainty of the oncological outcome have raised the concern that patients with locally advanced low rectal cancer with LPLNM could be over or under-treated. A comprehensive review of literature was performed, summarizing the current evidence on available modalities for predicting LPLNM, the role of LPLND in the management of advanced low rectal cancer and the available surgical approaches with their impact on surgical and oncological outcomes. LPLND is associated with increased operative time, blood loss and post-operative morbidity. The potential benefits for local disease control and survival still awaits high quality studies. There has been increasing number of reports of the use minimally invasive approaches in LPLND in an attempt to reduce post-operative complications. There is need for high quality evidence to define the role of LPLND in management of patients with advanced low rectal cancer.

Dynamic contrast-enhanced magnetic resonance imaging biomarkers predict chemotherapeutic responses and survival in primary central-nervous-system lymphoma

OBJECTIVES

To evaluate the utility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting the response of chemotherapy and clinical outcomes in primary central-nervous-system lymphoma (PCNSL) patients.

METHODS

DCE-MRI in 56 patients enrolled in a prospective study was performed at baseline and 30 days after treatment from 2016 to 2019. Multivariate logistic regression analyses were performed to assess risk factors for tumor responses. The predictive values of related parameters derived from DCE were analyzed via receiver operating characteristic (ROC) curve analysis. To evaluate prognostic factors, the Kaplan-Meier survival analysis with log-rank tests and Cox regression tests were analyzed.

RESULTS

K^trans and V_e were higher in the non-response group than in the response group (p < 0.05). The K^trans and the percentage of K^trans decreased after 30 days of treatment were independent predictors of chemotherapy responses (p = 0.034 and p = 0.019). ROC analysis indicated that the cut-off point of K^trans for predicting chemotherapeutic responses was 0.353 min^-1 (AUC, 0.941; 95% CI, 0.87-1; p < 0.001) and percentage of K^trans decreased after 30 days of treatment was 15.2% (AUC, 0.858; 95% CI, 0.742-0.970; p < 0.001). The greater decrease in K^trans correlated with a longer progression-free survival (PFS) (χ² = 13.203, p < 0.001). The higher K^trans was an independent predictor for shorter PFS (hazard ratio, 10.182; 95% CI, 2.510-41.300; p = 0.001).

CONCLUSIONS

K^trans and K^trans change measured by DCE-MRI were reliable biomarkers for predicting chemotherapy responses in PCNSL patients.

KEY POINTS

• Baseline K^trans and greater decrease in K^trans can predict chemotherapeutic efficacy. • DCE-MRI provides quantitative parameters reflecting the tumor microenvironment. • Targeted treatment therapy can be given with more evidence in the future.

Sex Differences and Tumor Blood Flow from Dynamic Susceptibility Contrast MRI Are Associated with Treatment Response after Chemoradiation and Long-term Survival in Rectal Cancer

Background MRI is the standard tool for rectal cancer staging. However, more precise diagnostic tests that can assess biologic tumor features decisive for treatment outcome are necessary. Tumor perfusion and hypoxia are two important features; however, no reference methods that measure these exist in clinical use. Purpose To assess the potential predictive and prognostic value of MRI-assessed rectal cancer perfusion, as a surrogate measure of hypoxia, for local treatment response and survival. Materials and Methods In this prospective observational cohort study, 94 study participants were enrolled from October 2013 to December 2017 (ClinicalTrials.gov: NCT01816607). Participants had histologically confirmed rectal cancer and underwent routine diagnostic MRI, an extended diffusion-weighted sequence, and a multiecho dynamic contrast agent-based sequence. Predictive and prognostic values of dynamic contrast-enhanced, dynamic susceptibility contrast (DSC), and intravoxel incoherent motion MRI were investigated with response to neoadjuvant treatment, progression-free survival, and overall survival as end points. Secondary objectives investigated potential sex differences in MRI parameters and relationship with lymph node stage. Statistical methods used were Cox regression, Student t test, and Mann-Whitney U test. Results A total of 94 study participants (mean age, 64 years ± 11 [standard deviation]; 61 men) were evaluated. Baseline tumor blood flow from DSC MRI was lower in patients who had poor local tumor response to neoadjuvant treatment (96 mL/min/100 g ± 33 for ypT2-4, 120 mL/min/100 g ± 21 for ypT0-1; P = .01), shorter progression-free survival (hazard ratio = 0.97; 95% confidence interval: 0.96, 0.98; P < .001), and shorter overall survival (hazard ratio = 0.98; 95% confidence interval: 0.98, 0.99; P < .001). Women had higher blood flow (125 mL/min/100 g ± 27) than men (74 mL/min/100 g ± 26, P < .001) at stage 4. Volume transfer constant and plasma volume from dynamic contrast-enhanced MRI as well as ΔR₂* peak and area under the curve for 30 and 60 seconds from DSC MRI were associated with local malignant lymph nodes (pN status). Median area under the curve for 30 seconds was 0.09 arbitrary units (au) ± 0.03 for pN1-2 and 0.19 au ± 0.12 for pN0 (P = .001). Conclusion Low tumor blood flow from dynamic susceptibility contrast MRI was associated with poor treatment response in study participants with rectal cancer. © RSNA, 2020 Online supplemental material is available for this article.

Radiomic Texture and Shape Descriptors of the Rectal Environment on Post-Chemoradiation T2-Weighted MRI are Associated with Pathologic Tumor Stage Regression in Rectal Cancers: A Retrospective, Multi-Institution Study

(1) Background: The relatively poor expert restaging accuracy of MRI in rectal cancer after neoadjuvant chemoradiation may be due to the difficulties in visual assessment of residual tumor on post-treatment MRI. In order to capture underlying tissue alterations and morphologic changes in rectal structures occurring due to the treatment, we hypothesized that radiomics texture and shape descriptors of the rectal environment (e.g., wall, lumen) on post-chemoradiation T2-weighted (T2w) MRI may be associated with tumor regression after neoadjuvant chemoradiation therapy (nCRT). (2) Methods: A total of 94 rectal cancer patients were retrospectively identified from three collaborating institutions, for whom a 1.5 or 3T T2w MRI was available after nCRT and prior to surgical resection. The rectal wall and the lumen were annotated by an expert radiologist on all MRIs, based on which 191 texture descriptors and 198 shape descriptors were extracted for each patient. (3) Results: Top-ranked features associated with pathologic tumor-stage regression were identified via cross-validation on a discovery set (n = 52, 1 institution) and evaluated via discriminant analysis in hold-out validation (n = 42, 2 institutions). The best performing features for distinguishing low (ypT0-2) and high (ypT3-4) pathologic tumor stages after nCRT comprised directional gradient texture expression and morphologic shape differences in the entire rectal wall and lumen. Not only were these radiomic features found to be resilient to variations in magnetic field strength and expert segmentations, a quadratic discriminant model combining them yielded consistent performance across multiple institutions (hold-out AUC of 0.73). (4) Conclusions: Radiomic texture and shape descriptors of the rectal wall from post-treatment T2w MRIs may be associated with low and high pathologic tumor stage after neoadjuvant chemoradiation therapy and generalized across variations between scanners and institutions.

Role of dynamic perfusion magnetic resonance imaging in patients with local advanced rectal cancer

BACKGROUND

The management of rectal cancer patients is mainly based on the use of the magnetic resonance imaging (MRI) technique as a diagnostic tool for both staging and restaging. After treatment, to date, the evaluation of complete response is based on the histopathology assessment by using different tumor regression grade (TRG) features (e.g., Dworak or Mandard classifications). While from the radiological point of view, the main attention for the prediction of a complete response after chemotherapy treatment focuses on MRI and the potential role of diffusion-weighted images and perfusion imaging represented by dynamic-contrast enhanced MRI. The main aim is to find a reliable tool to predict tumor response in comparison to histopathologic findings.

AIM

To investigate the value of dynamic contrast-enhanced perfusion-MRI parameters in the evaluation of the healthy rectal wall and tumor response to chemo-radiation therapy in patients with local advanced rectal cancer with histopathologic correlation.

METHODS

Twenty-eight patients with biopsy-proven rectal adenocarcinoma who underwent a dynamic contrast-enhanced MR study performed on a 1.5T MRI system (Achieva, Philips), before (MR1) and after chemoradiation therapy (MR2), were enrolled in this study. The protocol included T1 gadolinium enhanced THRIVE sequences acquired on axial planes. A dedicated workstation was used to generate color permeability maps. Region of interest was manually drawn on tumor tissue and normal rectal wall, hence the following parameters were calculated and statistically analyzed: Relative arterial enhancement (RAE), relative venous enhancement (RVE), relative late enhancement (RLE), maximum enhancement (ME), time to peak and area under the curve (AUC). Perfusion parameters were related to pathologic TRG (Mandard's criteria; TRG1 = complete regression, TRG5 = no regression).

RESULTS

Ten tumors (36%) showed complete or subtotal regression (TRG1-2) at histology and classified as responders; 18 tumors (64%) were classified as non-responders (TRG3-5). Perfusion MRI parameters were significantly higher in the tumor tissue than in the healthy tissue in MR1 (P < 0.05). At baseline (MR1), no significant difference in perfusion parameters was found between responders and non-responders. After chemo-radiation therapy, at MR2, responders showed significantly (P < 0.05) lower perfusion values [RAE (%) 54 ± 20; RVE (%) 73 ± 24; RLE (%): 82 ± 29; ME (%): 904 ± 429] compared to non-responders [RAE (%): 129 ± 45; RVE (%): 154 ± 39; RLE (%): 164 ± 35; ME (%): 1714 ± 427]. Moreover, in responders group perfusion values decreased significantly at MR2 [RAE (%): 54 ± 20; RVE (%): 73 ± 24; RLE (%): 82 ± 29; ME (%): 904 ± 429] compared to the corresponding perfusion values at MR1 [RAE (%): 115 ± 21; RVE (%): 119 ± 21; RLE (%): 111 ± 74; ME (%): 1060 ± 325]; (P < 0.05). Concerning the time-intensity curves, the AUC at MR2 showed significant difference (P = 0.03) between responders and non-responders [AUC (mm2 × 10-3) 121 ± 50 vs 258 ± 86], with lower AUC values of the tumor tissue in responders compared to non-responders. In non-responders, there were no significant differences between perfusion values at MR1 and MR2.

CONCLUSION

Dynamic contrast perfusion-MRI analysis represents a complementary diagnostic tool for identifying vascularity characteristics of tumor tissue in local advanced rectal cancer, useful in the assessment of treatment response.

Tumor segmentation analysis at different post-contrast time points: A possible source of variability of quantitative DCE-MRI parameters in locally advanced breast cancer

PURPOSE

to assess if tumor segmentation analysis performed at different post-contrast time points (TPs) on dynamic images could influence the extraction of dynamic contrast enhanced (DCE)-MRI parameters in locally advanced breast cancer (LABC), and potentially represent a source of variability.

METHOD

forty patients with forty-two LABC lesions were prospectively enrolled and underwent breast DCE-MRI examination at 3 T. On post-processed dynamic images, enhancing tumor lesions were manually segmented at four different TPs: at the first post-contrast dynamic image in which the lesion was appreciable (TP 1) and at 1, 5 and 10 min after contrast-agent administration (TPs 2, 3 and 4, respectively) and corresponding DCE-MRI parameters were extracted. Friedman's test followed by Bonferroni-adjusted Wilcoxon signed rank test for post-hoc analysis was used to compare DCE-MRI parameters. Intra- and inter-observer reliability of DCE-MRI parameters measurements was assessed using the Intraclass Correlation Coefficient (ICC) analysis.

RESULTS

Ktrans, Kep and iAUC were significantly higher when extracted from ROIs placed at TP1 and progressively decreased from TP 2-4. The intra-observer reliability ranged from good to excellent (ICC's: 0.894 to 0.990). The inter-observer reliability varied from moderate to excellent (0.770 to 0.942). The inter-observer reliability was significantly higher for Ktrans and Kep extracted at TPs1 and 2 as compared to TPs 3 and 4.

CONCLUSIONS

A significant variability of DCE-MRI quantitative parameters occurs when tumor segmentation is performed at different TPs. We suggest to performing tumor delineation at an established TP, preferably the earliest, in order to extract reliable and comparable DCE-MRI data.

Dynamic contrast-enhanced MRI model selection for predicting tumor aggressiveness in papillary thyroid cancers

The purpose of this study was to identify the optimal tracer kinetic model from T1 -weighted dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data and evaluate whether parameters estimated from the optimal model predict tumor aggressiveness determined from histopathology in patients with papillary thyroid carcinoma (PTC) prior to surgery. In this prospective study, 18 PTC patients underwent pretreatment DCE-MRI on a 3 T MR scanner prior to thyroidectomy. This study was approved by the institutional review board and informed consent was obtained from all patients. The two-compartment exchange model, compartmental tissue uptake model, extended Tofts model (ETM) and standard Tofts model were compared on a voxel-wise basis to determine the optimal model using the corrected Akaike information criterion (AICc) for PTC. The optimal model is the one with the lowest AICc. Statistical analysis included paired and unpaired t-tests and a one-way analysis of variance. Bonferroni correction was applied for multiple comparisons. Receiver operating characteristic (ROC) curves were generated from the optimal model parameters to differentiate PTC with and without aggressive features, and AUCs were compared. ETM performed best with the lowest AICc and the highest Akaike weight (0.44) among the four models. ETM was preferred in 44% of all 3419 voxels. The ETM estimates of Ktrans in PTCs with the aggressive feature extrathyroidal extension (ETE) were significantly higher than those without ETE (0.78 ± 0.29 vs. 0.34 ± 0.18 min-1 , P = 0.005). From ROC analysis, cut-off values of Ktrans , ve and vp , which discriminated between PTCs with and without ETE, were determined at 0.45 min-1 , 0.28 and 0.014 respectively. The sensitivities and specificities were 86 and 82% (Ktrans ), 71 and 82% (ve ), and 86 and 55% (vp ), respectively. Their respective AUCs were 0.90, 0.71 and 0.71. We conclude that ETM Ktrans has shown potential to classify tumors with and without aggressive ETE in patients with PTC.