Standardized Index of Shape (SIS): a quantitative DCE-MRI parameter to discriminate responders by non-responders after neoadjuvant therapy in LARC. Eur Radiol. 2015;25:1935-1945. [PMID: 25577525 DOI: 10.1007/s00330-014-3581-3]

Scientific Status Quo of Small Renal Lesions: Diagnostic Assessment and Radiomics

Background: Small renal masses (SRMs) are defined as contrast-enhanced renal lesions less than or equal to 4 cm in maximal diameter, which can be compatible with stage T1a renal cell carcinomas (RCCs). Currently, 50-61% of all renal tumors are found incidentally. Methods: The characteristics of the lesion influence the choice of the type of management, which include several methods SRM of management, including nephrectomy, partial nephrectomy, ablation, observation, and also stereotactic body radiotherapy. Typical imaging methods available for differentiating benign from malignant renal lesions include ultrasound (US), contrast-enhanced ultrasound (CEUS), computed tomography (CT), and magnetic resonance imaging (MRI). Results: Although ultrasound is the first imaging technique used to detect small renal lesions, it has several limitations. CT is the main and most widely used imaging technique for SRM characterization. The main advantages of MRI compared to CT are the better contrast resolution and tissue characterization, the use of functional imaging sequences, the possibility of performing the examination in patients allergic to iodine-containing contrast medium, and the absence of exposure to ionizing radiation. For a correct evaluation during imaging follow-up, it is necessary to use a reliable method for the assessment of renal lesions, represented by the Bosniak classification system. This classification was initially developed based on contrast-enhanced CT imaging findings, and the 2019 revision proposed the inclusion of MRI features; however, the latest classification has not yet received widespread validation. Conclusions: The use of radiomics in the evaluation of renal masses is an emerging and increasingly central field with several applications such as characterizing renal masses, distinguishing RCC subtypes, monitoring response to targeted therapeutic agents, and prognosis in a metastatic context.

Radiomics and artificial intelligence analysis by T2-weighted imaging and dynamic contrast-enhanced magnetic resonance imaging to predict Breast Cancer Histological Outcome

OBJECTIVE

The objective of the study was to evaluate the accuracy of radiomics features obtained by MR images to predict Breast Cancer Histological Outcome.

METHODS

A total of 217 patients with malignant lesions were analysed underwent MRI examinations. Considering histological findings as the ground truth, four different types of findings were used in both univariate and multivariate analyses: (1) G1 + G2 vs G3 classification; (2) presence of human epidermal growth factor receptor 2 (HER2 + vs HER2 -); (3) presence of the hormone receptor (HR + vs HR -); and (4) presence of luminal subtypes of breast cancer.

RESULTS

The best accuracy for discriminating HER2 + versus HER2 - breast cancers was obtained considering nine predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 88% on validation set). The best accuracy for discriminating HR + versus HR - breast cancers was obtained considering nine predictors by T2-weighted subtraction images and a decision tree (accuracy of 90% on validation set). The best accuracy for discriminating G1 + G2 versus G3 breast cancers was obtained considering 16 predictors by early phase T1-weighted subtraction images in a linear regression model with an accuracy of 75%. The best accuracy for discriminating luminal versus non-luminal breast cancers was obtained considering 27 predictors by early phase T1-weighted subtraction images and a decision tree (accuracy of 94% on validation set).

CONCLUSIONS

The combination of radiomics analysis and artificial intelligence techniques could be used to support physician decision-making in prediction of Breast Cancer Histological Outcome.

Diffusion and Perfusion Imaging in Rectal Cancer Restaging

The assessment of tumor response, after neoadjuvant radiochemotherapy (n-CRT), permits the stratification of patients for the proper therapeutical management. Although histopathology analysis of the surgical speciemen is considered the gold standard for assessing tumor response, magnetic resonance imaging (MRI), with its significant developments in technical imaging, have allowed an increase in accuracy for the evaluation of response. MRI provides a radiological tumor regression grade (mrTRG) that is correlated with the pathologic tumor regression grade (pTRG). Functional MRI parameters have additional impending in early prediction of the efficacy of therapy. Some of functional methodologies are already part of clinical practice: diffusion-weighted MRI (DW-MRI) and perfusion imaging (dynamic contrast enhanced MRI [DCE-MRI]).

Colorectal liver metastases patients prognostic assessment: prospects and limits of radiomics and radiogenomics

In this narrative review, we reported un up-to-date on the role of radiomics to assess prognostic features, which can impact on the liver metastases patient treatment choice. In the liver metastases patients, the possibility to assess mutational status (RAS or MSI), the tumor growth pattern and the histological subtype (NOS or mucinous) allows a better treatment selection to avoid unnecessary therapies. However, today, the detection of these features require an invasive approach. Recently, radiomics analysis application has improved rapidly, with a consequent growing interest in the oncological field. Radiomics analysis allows the textural characteristics assessment, which are correlated to biological data. This approach is captivating since it should allow to extract biological data from the radiological images, without invasive approach, so that to reduce costs and time, avoiding any risk for the patients. Several studies showed the ability of Radiomics to identify mutational status, tumor growth pattern and histological type in colorectal liver metastases. Although, radiomics analysis in a non-invasive and repeatable way, however features as the poor standardization and generalization of clinical studies results limit the translation of this analysis into clinical practice. Clear limits are data-quality control, reproducibility, repeatability, generalizability of results, and issues related to model overfitting.

Machine Learning Approaches with Textural Features to Calculate Breast Density on Mammography

BACKGROUND

breast cancer (BC) is the world's most prevalent cancer in the female population, with 2.3 million new cases diagnosed worldwide in 2020. The great efforts made to set screening campaigns, early detection programs, and increasingly targeted treatments led to significant improvement in patients' survival. The Full-Field Digital Mammograph (FFDM) is considered the gold standard method for the early diagnosis of BC. From several previous studies, it has emerged that breast density (BD) is a risk factor in the development of BC, affecting the periodicity of screening plans present today at an international level.

OBJECTIVE

in this study, the focus is the development of mammographic image processing techniques that allow the extraction of indicators derived from textural patterns of the mammary parenchyma indicative of BD risk factors.

METHODS

a total of 168 patients were enrolled in the internal training and test set while a total of 51 patients were enrolled to compose the external validation cohort. Different Machine Learning (ML) techniques have been employed to classify breasts based on the values of the tissue density. Textural features were extracted only from breast parenchyma with which to train classifiers, thanks to the aid of ML algorithms.

RESULTS

the accuracy of different tested classifiers varied between 74.15% and 93.55%. The best results were reached by a Support Vector Machine (accuracy of 93.55% and a percentage of true positives and negatives equal to TPP = 94.44% and TNP = 92.31%). The best accuracy was not influenced by the choice of the features selection approach. Considering the external validation cohort, the SVM, as the best classifier with the 7 features selected by a wrapper method, showed an accuracy of 0.95, a sensitivity of 0.96, and a specificity of 0.90.

CONCLUSIONS

our preliminary results showed that the Radiomics analysis and ML approach allow us to objectively identify BD.

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

INTRODUCTION

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

AREAS COVERED

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

EXPERT OPINION

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

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

Background

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

Methods

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

Results

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

Conclusions

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

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

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

Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging

Dynamic contrast-enhanced (DCE) imaging is a non-invasive technique used for the evaluation of tissue vascularity features through imaging series acquisition after contrast medium administration. Over the years, the study technique and protocols have evolved, seeing a growing application of this method across different imaging modalities for the study of almost all body districts. The main and most consolidated current applications concern MRI imaging for the study of tumors, but an increasing number of studies are evaluating the use of this technique also for inflammatory pathologies and functional studies. Furthermore, the recent advent of artificial intelligence techniques is opening up a vast scenario for the analysis of quantitative information deriving from DCE. The purpose of this article is to provide a comprehensive update on the techniques, protocols, and clinical applications - both established and emerging - of DCE in whole-body imaging.

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.

Validation of the standardized index of shape tool to analyze DCE-MRI data in the assessment of neo-adjuvant therapy in locally advanced rectal cancer

PURPOSE

Standardized index of shape (SIS) tool validation to examine dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) in preoperative chemo-radiation therapy (pCRT) assessment of locally advanced rectal cancer (LARC) in order to guide the surgeon versus more or less conservative treatment.

MATERIALS AND METHODS

A total of 194 patients (January 2008-November 2020), with III-IV locally advanced rectal cancer and subjected to pCRT were included. Three expert radiologists performed DCE-MRI analysis using SIS tool. Degree of absolute agreement among measurements, degree of consistency among measurements, degree of reliability and level of variability were calculated. Patients with a pathological tumour regression grade (TRG) 1 or 2 were classified as major responders (complete responders have TRG 1).

RESULTS

Good significant correlation was obtained between SIS measurements (range 0.97-0.99). The degree of absolute agreement ranges from 0.93 to 0.99, the degree of consistency from 0.81 to 0.9 and the reliability from 0.98 to 1.00 (p value <  < 0.001). The variability coefficient ranges from 3.5% to 26%. SIS value obtained to discriminate responders by non-responders a sensitivity of 95.9%, a specificity of 84.7% and an accuracy of 91.8% while to detect complete responders, a sensitivity of 99.2%, a specificity of 63.9% and an accuracy of 86.1%.

CONCLUSION

SIS tool is suitable to assess pCRT response both to identify major responders and complete responders in order to guide the surgeon versus more or less conservative treatment.

Machine Learning-Based Integration of Prognostic Magnetic Resonance Imaging Biomarkers for Myometrial Invasion Stratification in Endometrial Cancer

BACKGROUND

Estimation of the depth of myometrial invasion (MI) in endometrial cancer is pivotal in the preoperatively staging. Magnetic resonance (MR) reports suffer from human subjectivity. Multiparametric MR imaging radiomics and parameters may improve the diagnostic accuracy.

PURPOSE

To discriminate between patients with MI ≥ 50% using a machine learning-based model combining texture features and descriptors from preoperatively MR images.

STUDY TYPE

Retrospective.

POPULATION

One hundred forty-three women with endometrial cancer were included. The series was split into training (n = 107, 46 with MI ≥ 50%) and test (n = 36, 16 with MI ≥ 50%) cohorts.

FIELD STRENGTH/SEQUENCES

Fast spin echo T2-weighted (T2W), diffusion-weighted (DW), and T1-weighted gradient echo dynamic contrast-enhanced (DCE) sequences were obtained at 1.5 or 3 T magnets.

ASSESSMENT

Tumors were manually segmented slice-by-slice. Texture metrics were calculated from T2W and ADC map images. Also, the apparent diffusion coefficient (ADC), wash-in slope, wash-out slope, initial area under the curve at 60 sec and at 90 sec, initial slope, time to peak and peak amplitude maps from DCE sequences were obtained as parameters. MR diagnostic models using single-sequence features and a combination of features and parameters from the three sequences were built to estimate MI using Adaboost methods. The pathological depth of MI was used as gold standard.

STATISTICAL TEST

Area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, accuracy, positive predictive value, negative predictive value, precision and recall were computed to assess the Adaboost models performance.

RESULTS

The diagnostic model based on the features and parameters combination showed the best performance to depict patient with MI ≥ 50% in the test cohort (accuracy = 86.1% and AUROC = 87.1%). The rest of diagnostic models showed a worse accuracy (accuracy = 41.67%-63.89% and AUROC = 41.43%-63.13%).

DATA CONCLUSION

The model combining the texture features from T2W and ADC map images with the semi-quantitative parameters from DW and DCE series allow the preoperative estimation of myometrial invasion. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 3.

Assessing tumor response to neoadjuvant chemoradiation in rectal cancer with rectoscopy and 18F-FDG PET/CT: results from a prospective series

INTRODUCTION

rectoscopy and 18F-FDG PET/CT as a diagnostic algorithm for the assessment of tumor response in rectal cancer after neoadjuvant chemoradiation therapy (CRT) is very useful.

MATERIAL AND METHODS

this was a prospective longitudinal study in patients with locally advanced rectal cancer treated with neoadjuvant CRT. Patients were assessed after CRT completion with a digital rectal examination, proctoscopy and 18F-FDG PET/CT. Patients were subdivided as clinical (cCR) or radiologic (rCR) responders and non-responders according to tumor response. Clinical and radiological re-assessment was compared with the surgical specimen. Pathological tumor regression (pCR) grade was determined according to Mandard's classification. Of the 68 patients included, 15 (22 %) presented pCR in the surgical specimen and tumor persistence (non-PCR) was detected in the remaining 53 (78 %). Clinical assessment (DRE+ rectoscopy) identified 15 patients as cCR and 53 as non-cCR, two were false positives and two were false negatives. The overall accuracy was 94 %. 18F-FDG PET/CT identified 18 patients as rCR and 50 as non-rCR, one was a false positive and four were false negatives. The overall accuracy was 92 %. A combination of clinical findings and 18F-FDG PET/CT resulted in an accuracy of 96 %. The combination of clinical findings + 18F-FDG PET/CT was able to correctly identify all cases of pCR, with the exception of one case that presented a tumor regression of 80 %. In this series, 18F-PET-CT and clinical assessment had excellent accuracies in differentiating PCR from non-PCR after CRT completion. PET-CT combined with clinical assessment had a better accuracy than both modalities independently. 18F-FDG PET/CT is a valid tool that complements the clinical assessment of tumor response.

Introduction to Special Issue of Radiology and Imaging of Cancer

The increase in knowledge in oncology and the possibility of creating personalized medicine by selecting a more appropriate therapy related to the different tumor subtypes, as well as the management of patients with cancer within a multidisciplinary team has improved the clinical outcomes [...].

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.

Textural radiomic features and time-intensity curve data analysis by dynamic contrast-enhanced MRI for early prediction of breast cancer therapy response: preliminary data

BACKGROUND

To investigate the potential of semiquantitative time-intensity curve parameters compared to textural radiomic features on arterial phase images by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for early prediction of breast cancer neoadjuvant therapy response.

METHODS

A retrospective study of 45 patients subjected to DCE-MRI by public datasets containing examination performed prior to the start of treatment and after the treatment first cycle ('QIN Breast DCE-MRI' and 'QIN-Breast') was performed. In total, 11 semiquantitative parameters and 50 texture features were extracted. Non-parametric test, receiver operating characteristic analysis with area under the curve (ROC-AUC), Spearman correlation coefficient, and Kruskal-Wallis test with Bonferroni correction were applied.

RESULTS

Fifteen patients with pathological complete response (pCR) and 30 patients with non-pCR were analysed. Significant differences in median values between pCR patients and non-pCR patients were found for entropy, long-run emphasis, and busyness among the textural features, for maximum signal difference, washout slope, washin slope, and standardised index of shape among the dynamic semiquantitative parameters. The standardised index of shape had the best results with a ROC-AUC of 0.93 to differentiate pCR versus non-pCR patients.

CONCLUSIONS

The standardised index of shape could become a clinical tool to differentiate, in the early stages of treatment, responding to non-responding patients.

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

PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

A compact solution for estimation of physiological parameters from ultrafast prostate dynamic contrast enhanced MRI

The Tofts pharmacokinetic model requires multiple calculations for analysis of dynamic contrast enhanced (DCE) MRI. In addition, the Tofts model may not be appropriate for the prostate. This can result in error propagation that reduces the accuracy of pharmacokinetic measurements. In this study, we present a compact solution allowing estimation of physiological parameters K ^trans and v _e from ultrafast DCE acquisitions, without fitting DCE-MRI data to the standard Tofts pharmacokinetic model. Since the standard Tofts model can be simplified to the Patlak model at early times when contrast efflux from the extravascular extracellular space back to plasma is negligible, K ^trans can be solved explicitly for a specific time. Further, v _e can be estimated directly from the late steady-state signal using the derivative form of Tofts model. Ultrafast DCE-MRI data were acquired from 18 prostate cancer patients on a Philips Achieva 3T-TX scanner. Regions-of-interest (ROIs) for prostate cancer, normal tissue, gluteal muscle, and iliac artery were manually traced. The contrast media concentration as function of time was calculated over each ROI using gradient echo signal equation with pre-contrast tissue T1 values, and using the 'reference tissue' model with a linear approximation. There was strong correlation (r  =  0.88-0.91, p   <  0.0001) between K ^trans extracted from the Tofts model and K ^trans estimated from the compact solution for prostate cancer and normal tissue. Additionally, there was moderate correlation (r  =  0.65-0.73, p   <  0.0001) between extracted versus estimated v _e. Bland-Altman analysis showed moderate to good agreement between physiological parameters extracted from the Tofts model and those estimated from the compact solution with absolute bias less than 0.20 min^-1 and 0.10 for K ^trans and v _e, respectively. The compact solution may decrease systematic errors and error propagation, and could increase the efficiency of clinical workflow. The compact solution requires high temporal resolution DCE-MRI due to the need to adequately sample the early phase of contrast media uptake.

Assessing response to neo-adjuvant therapy in locally advanced rectal cancer using Intra-voxel Incoherent Motion modelling by DWI data and Standardized Index of Shape from DCE-MRI

Background:

Our aim was to investigate preoperative chemoradiation therapy (pCRT) response in locally advanced rectal cancer (LARC) comparing standardized index of shape (SIS) obtained from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with intravoxel-incoherent-motion-modelling-derived parameters by diffusion-weighted imaging (DWI).

Materials and methods:

Eighty-eight patients with LARC were subjected to MRI before and after pCRT. Apparent diffusion coefficient (ADC), tissue diffusion (D_t), pseudodiffusion (D_p) and perfusion fraction (f) were calculated and percentage changes ∆ADC, ∆D_t, ∆D_p, ∆f were computed. SIS was derived comparing DCE-MRI pre- and post-pCRT. Nonparametric tests and receiver operating characteristic (ROC) curves were performed.

Results:

A total of 52 patients were classified as responders (tumour regression grade; TRG ⩽ 2) and 36 as not-responders (TRG > 3). Mann–Whitney U test showed statistically significant differences in SIS, ∆ADC and ∆D_t between responders and not-responders and between complete responders (19 patients with TRG = 1) versus incomplete responders. The best parameters to discriminate responders by nonresponders were SIS and ∆ADC, with an accuracy of 91% and 82% (cutoffs of −5.2% and 18.7%, respectively); the best parameters to detect pathological complete responders were SIS, ∆f and ∆D_p with an accuracy of 78% (cutoffs of 38.5%, 60.0% and 83.0%, respectively). No increase of performance was observed by combining linearly each possible couple of parameters or combining all parameters.

Conclusion:

SIS allows assessment of preoperative treatment response with high accuracy guiding the surgeon versus more or less conservative treatment. DWI-derived parameters reached less accuracy compared with SIS and combining linearly DCE- and DWI-derived parameters; no increase of accuracy was obtained.

Value of MRI morphologic features with pT1-2 rectal cancer in determining lymph node metastasis

BACKGROUND AND OBJECTIVES

To investigate the different features between metastatic lymph node and nonmetastatic lymph node on magnetic resonance imaging (MRI) and the relationship between the rectal lesion and lymph node metastasis (LNM).

METHODS

Eighty-two patients with retrospectively consecutive pT1-2 stage rectal cancer in 2016 were divided into lymph node metastasis (LNM+) and lymph node nonmetastasis (LNM-) group based on their histopathologic examinations. We evaluated the following features of lymph nodes: number, shape, signal heterogeneity, border, and diameter of the largest lymph node on T2-weight images. We also calculated tumor apparent diffusion coefficient ratio and tumor percent enhancement. Fisher's exact test was applied for inspecting lymph node numbers on MRI and logistic regression analysis in examining risk factors for LNM.

RESULTS

The MR-LN number was significantly different between the LNM+ and LNM- group (median: 4 vs 1, P = 0.001). Multivariate logistic regression analysis exhibited that the diameter of the largest lymph node and the tumor percent enhancement of the arterial phase were independent risk factors of LNM (P = 0.005 vs 0.021, respectively).

CONCLUSIONS

The largest lymph node's diameter and the tumor percent enhancement of arterial phase on MRI were helpful in determining LNM in pT1-2 rectal cancer.

A radiologist's point of view in the presurgical and intraoperative setting of colorectal liver metastases

Multidisciplinary management of patients with metastatic colorectal cancer requires in each phase an adequate choice of the most appropriate imaging modality. The first challenging step is liver lesions detection and characterization, using several imaging modality ultrasound, computed tomography, magnetic resonance and positron emission tomography. The criteria to establish the metastases resectability have been modified. Not only the lesions number and site but also the functional volume remnant after surgery and the quality of the nontumoral liver must be taken into account. Radiologists should identify the liver functional volume remnant and during liver surgical procedures should collaborate with the surgeon to identify all lesions, including those that disappeared after the therapy, using intraoperative ultrasound with or without contrast medium.

Response to neoadjuvant chemoradiotherapy for locally advanced rectum cancer: Texture analysis of dynamic contrast-enhanced MRI

BACKGROUND

Tumor heterogeneity can be assessed by texture analysis (TA). TA has been applied using diffusion-weighted imaging and apparent diffusion coefficient maps to predict pathological responses to preoperative chemoradiation therapy (CRT) in patients with locally advanced rectal cancer (LARC).

PURPOSE

To evaluate the texture parameters obtained from K ^trans maps derived from dynamic contrast-enhanced (DCE)-MRI for predicting pathological responses to preoperative CRT for LARCs.

STUDY TYPE

Retrospective.

POPULATION

Altogether, 83 patients (26 women, 57 men) with rectal cancer met the inclusion criteria.

FIELD STRENGTH/SEQUENCE

3.0T/T₁ -weighted DCE-MRI sequence.

ASSESSMENT

After CRT, each tumor was assessed by a pathologist who assigned a tumor regression grade (TRG), thereby identifying pathologically complete responders (pCR; TRG 1) and good responders (GR; TRG1 + TRG2). TA was then applied to the DCE-MRI K ^trans maps. The K ^trans value, several TA parameters, and tumor volumes were calculated.

STATISTICAL TESTS

The Shapiro-Wilk test was used to verify that the data had normal distribution. Results of parameters measured before and after CRT were compared using paired-sample t-tests. Value changes of each parameter in the combined pCR/GR group were compared using independent sample t-tests. Receiver operating characteristic curves and areas under the curve (AUC) were calculated to assess the diagnostic performance of each parameter related to CRT effectiveness.

RESULTS

There were 15 pCR (16.9%) and 21 GR (25.3%) patients. Tumor volume, mean K ^trans , entropy, and correlation decreased and energy values increased significantly in these groups compared with those of the non-PCR and non-GR groups. ΔCorrelation (Δcorrelation = postcorrelation - precorrelation) was found to be a valuable parameter for identifying pCR/GR patients (AUC 0.895, sensitivity 86.7%, specificity 81.8%).

DATA CONCLUSION

TA parameters from the DCE-MRI K ^trans map can predict the efficacy of CRT for treating LARCs. Also, Δcorrelation may be useful for identifying patients who will be responsive to CRT.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;49:885-893.

DCE-MRI time-intensity curve visual inspection to assess pathological response after neoadjuvant therapy in locally advanced rectal cancer

PURPOSE

To investigate the potential of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to discriminate responder from non-responder patients after preoperative chemoradiotherapy (pCRT) in locally advanced rectal cancer (LARC).

MATERIALS AND METHODS

One hundred and fifty-eight consecutive patients were enrolled in this prospective study. We compared morphological MRI (mMRI) using T2-weighted images about tumor presence and invasiveness, and functional DCE-MRI using time-intensity curve (TIC) visual inspection (qMRI), classifying TIC shape into three types: type 1, persistent enhancement; type 2, high enhancement with plateau; type 3, high enhancement with wash-out. Clinical TNM was obtained before and after CRT by radiological consensus of two expert radiologists. Pathological tumor-nodes-metastasis classification and tumor regression grade (TRG) were confirmed as the golden standard. Non-parametric test, sensitivity, specificity, and positive and negative predictive values were calculated.

RESULTS

Ninety-eight patients (62%) were classified as responders (TRG ≤ 2), while 60 (38%) were classified as non-responders. Sensitivity, specificity, and accuracy were 52, 78, and 62% for mMRI, and 81, 85, and 82% for qMRI, respectively.

CONCLUSIONS

TIC visual inspection may be one of the potential biomarkers over morphological analysis using DCE-MRI data to assess pathological response after pCRT in LARC.

Rectal cancer MRI: protocols, signs and future perspectives radiologists should consider in everyday clinical practice

Abstract

Magnetic resonance imaging (MRI) allows to non-invasively evaluate rectal cancer staging and to assess the presence of “prognostic signs” such as the distance from the anorectal junction, the mesorectal fascia infiltration and the extramural vascular invasion. Moreover, MRI plays a crucial role in the assessment of treatment response after chemo-radiation therapy, especially considering the growing interest in the new conservative policy (wait and see, minimally invasive surgery). We present a practical overview regarding the state of the art of the MRI protocol, the main signs that radiologists should consider for their reports during their clinical activity and future perspectives.

Teaching Points

• MRI protocol for rectal cancer staging and re-staging.

• MRI findings that radiologists should consider for reports during everyday clinical activity.

• Perspectives regarding the development of latest technologies.

Standardized Index of Shape (DCE-MRI) and Standardized Uptake Value (PET/CT): Two quantitative approaches to discriminate chemo-radiotherapy locally advanced rectal cancer responders under a functional profile

Purpose

To investigate dynamic contrast enhanced-MRI (DCE-MRI) in the preoperative chemo-radiotherapy (CRT) assessment for locally advanced rectal cancer (LARC) compared to¹⁸F-fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT).

Methods

75 consecutive patients with LARC were enrolled in a prospective study. DCE-MRI analysis was performed measuring SIS: linear combination of percentage change (Δ) of maximum signal difference (MSD) and wash-out slope (WOS). ¹⁸F-FDG PET/CT analysis was performed using SUV maximum (SUV_max). Tumor regression grade (TRG) were estimated after surgery. Non-parametric tests, receiver operating characteristic were evaluated.

Results

55 patients (TRG1-2) were classified as responders while 20 subjects as non responders. ΔSIS reached sensitivity of 93%, specificity of 80% and accuracy of 89% (cut-off 6%) to differentiate responders by non responders, sensitivity of 93%, specificity of 69% and accuracy of 79% (cut-off 30%) to identify pathological complete response (pCR). Therapy assessment via ΔSUV_max reached sensitivity of 67%, specificity of 75% and accuracy of 70% (cut-off 60%) to differentiate responders by non responders and sensitivity of 80%, specificity of 31% and accuracy of 51% (cut-off 44%) to identify pCR.

Conclusions

CRT response assessment by DCE-MRI analysis shows a higher predictive ability than ¹⁸F-FDG PET/CT in LARC patients allowing to better discriminate significant and pCR.

Magnetic resonance tumor regression grade (MR-TRG) to assess pathological complete response following neoadjuvant radiochemotherapy in locally advanced rectal cancer

This study aims to evaluate the feasibility of a magnetic resonance (MR) automatic method for quantitative assessment of the percentage of fibrosis developed within locally advanced rectal cancers (LARC) after neoadjuvant radiochemotherapy (RCT). A total of 65 patients were enrolled in the study and MR studies were performed on 3.0 Tesla scanner; patients were followed-up for 30 months. The percentage of fibrosis was quantified on T2-weighted images, using automatic K-Means clustering algorithm. According to the percentage of fibrosis, an optimal cut-off point for separating patients into favorable and unfavorable pathologic response groups was identified by ROC analysis and tumor regression grade (MR-TRG) classes were determined and compared to histopathologic TRG. An optimal cut-off point of 81% of fibrosis was identified to differentiate between favorable and unfavorable pathologic response groups resulting in a sensitivity of 78.26% and a specificity of 97.62% for the identification of complete responders (CRs). Interobserver agreement was good (0.85). The agreement between P-TRG and MR-TRG was excellent (0.923). Significant differences in terms of overall survival (OS) and disease free survival (DFS) were found between favorable and unfavorable pathologic response groups. The automatic quantification of fibrosis determined by MR is feasible and reproducible.

Magnetic Resonance Imaging Evaluation in Neoadjuvant Therapy of Locally Advanced Rectal Cancer: A Systematic Review

Background

The aim of the study was to present an update concerning several imaging modalities in diagnosis, staging and pre-surgery treatment response assessment in locally advanced rectal cancer (LARC). Modalities include: traditional morphological magnetic resonance imaging (MRI), functional MRI such as dynamic contrast enhanced MRI (DCE-MRI) and diffusion weighted imaging (DWI). A systematic review about the diagnostic accuracy in neoadjuvant therapy response assessment of MRI, DCE-MRI, DWI and Positron Emission Tomography/Computed Tomography (PET/CT) has been also reported.

Methods

Several electronic databases were searched including PubMed, Scopus, Web of Science, and Google Scholar. All the studies included in this review reported findings about therapy response assessment in LARC by means of MRI, DCE-MRI, DWI and PET/CT with details about diagnostic accuracy, true and false negatives, true and false positives. Forest plot and receiver operating characteristic (ROC) curves analysis were performed. Risk of bias and the applicability at study level were calculated.

Results

Twenty-five papers were identified. ROC curves analysis demonstrated that multimodal imaging integrating morphological and functional MRI features had the best accuracy both in term of sensitivity and specificity to evaluate preoperative therapy response in LARC. DCE-MRI following to PET/CT showed high diagnostic accuracy and their results are also more reliable than conventional MRI and DWI alone.

Conclusions

Morphological MRI is the modality of choice for rectal cancer staging permitting a correct assessment of the disease extent, of the lymph node involvement, of the mesorectal fascia and of the sphincter complex for surgical planning. Multimodal imaging and functional DCE-MRI may also help in the assessment of treatment response allowing to guide the surgeon versus conservative strategies and/or tailored approach such as “wait and see” policy.

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

PURPOSE

Aim was to perform a systematic review to evaluate the clinical value of dynamic contrast-enhanced (DCE) MRI in rectal cancer.

METHODS AND MATERIALS

A systematic search was performed on Pubmed, Embase and the Cochrane library. Studies that evaluated DCE-MRI for tumour aggressiveness, primary staging and restaging after chemoradiation (CRT) were included. Information on population, DCE technique, DCE parameters and outcome (angiogenesis, staging and response) were extracted.

RESULTS

19 studies were identified; 10 evaluated quantitative analyses, 6 semiquantitative analyses and 3 evaluated both. 8 studies evaluated correlation between DCE-parameters and angiogenesis or tumour aggressiveness, 11 studies evaluated response prediction pre- and post-CRT. Semiquantitative washin parameters showed a significantly positive correlation with angiogenesis, while for quantitative analyses conflicting results were found. Conflicting results were also reported for the correlation between DCE parameters and tumour aggressiveness: both higher and lower vascularity in more aggressive tumours are reported, while some studies report no correlation. Six studies showed a predictive value of Ktrans for response. A high Ktrans pre-CRT was significantly correlated with a complete/good response, but the reported pre-CRT Ktrans varied substantially (0.36-1.93). After CRT a reduction in Ktrans of 32%-36% was significantly associated with response. For semiquantitative analyses pre-CRT late slope was reported to be significantly lower in good responders, however only few studies exist on semiquantitative analyses of post-CRT DCE-MRI.

CONCLUSION

DCE-MRI in rectal cancer is promising mainly for prediction and assessment of response to CRT, where a high pre-CRT Ktrans and a decrease in Ktrans are significantly predictive for response.

Correlation between quantitative and semiquantitative parameters in DCE-MRI with a blood pool agent in rectal cancer: can semiquantitative parameters be used as a surrogate for quantitative parameters?

PURPOSE

The aim of this study was to assess correlation between quantitative and semiquantitative parameters in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in rectal cancer patients, both in a primary staging and restaging setting.

MATERIALS AND METHODS

Nineteen patients were included with DCE-MRI before and/or after neoadjuvant therapy. DCE-MRI was performed with gadofosveset trisodium (Ablavar^®, Lantheus Medical Imaging, North Billerica, Massachusetts, USA). Regions of interest were placed in the tumor and quantitative parameters were extracted with Olea Sphere 2.2 software permeability module using the extended Tofts model. Semiquantitative parameters were calculated on a pixel-by-pixel basis. Spearman rank correlation tests were used for assessment of correlation between parameters. A p value ≤0.05 was considered statistically significant.

RESULTS

Strong positive correlations were found between mean peak enhancement and mean K _trans: 0.79 (all patients, p<0.0001), 0.83 (primary staging, p = 0.003), and 0.81 (restaging, p = 0.054). Mean wash-in correlated significantly with mean V _p and K _ep (0.79 and 0.58, respectively, p<0.0001 and p = 0.009) in all patients. Mean wash-in showed a significant correlation with mean K _ep (0.67, p = 0.033) in the primary staging group. On the restaging MRI, mean wash-in only strongly correlated with mean V _p (0.81, p = 0.054).

CONCLUSION

This study shows a strong correlation between quantitative and semiquantitative parameters in DCE-MRI for rectal cancer. Peak enhancement correlates strongly with K _trans and wash-in showed strong correlation with V _p and K _ep. These parameters have been reported to predict tumor aggressiveness and response in rectal cancer. Therefore, semiquantitative analyses might be a surrogate for quantitative analyses.

Diagnostic performance of magnetic resonance imaging and 3D endoanal ultrasound in detection, staging and assessment post treatment, in anal cancer

We compared Magnetic Resonance Imaging (MRI) and 3D Endoanal Ultrasound (EAUS) imaging performance to confirm anal carcinoma and to monitor treatment response.58 patients with anal cancer were retrospectively enrolled. All patients underwent clinical examination, anoscopic examination; EAUS and contrast-enhanced MRI study before and after treatment. Four radiologists evaluated the presence of lesions, using a 4-point confidence scale, features of the lesion and nodes on EAUS images, T1-weighted (T1-W), T2-weighted (T2-W) and diffusion-weighted images (DWI) signal intensity (SI), the apparent diffusion coefficient (ADC) map for nodes and lesion, as well as enhancement pattern during dynamic MRI were assessed.All lesions were detected by EAUS while MRI detected 93.1% of anal cancer. MRI showed a good correlation with EAUS, anoscopy and clinical examination. The residual tissue not showed significant difference in EAUS assessment and T2-W SI in pre and post treatment. We found significant difference in dynamic study, in SI of DWI, in ADC map and values among responder's patients in pre and post treatment. The neoplastic nodes were hypoecoic on EAUS, with hyperintense signal on T2-W sequences and hypointense signal on T1-W. The neoplastic nodes showed SI on DWI sequences and ADC value similar to anal cancer. We found significant difference in nodes status in pre and post therapy on DWI data.3D EAUS and MRI are accurate techniques in anal cancer staging, although EAUS is more accurate than MRI for T1 stage. MRI allows correct detection of neoplastic nodes and can properly stratify patients into responders or non responders.

Rectal Cancer: Assessment of Neoadjuvant Chemoradiation Outcome based on Radiomics of Multiparametric MRI

PURPOSE

To evaluate multiparametric MRI features in predicting pathologic response after preoperative chemoradiation therapy (CRT) for locally advanced rectal cancer (LARC).

EXPERIMENTAL DESIGN

Forty-eight consecutive patients (January 2012-November 2014) receiving neoadjuvant CRT were enrolled. All underwent anatomical T1/T2, diffusion-weighted MRI (DWI) and dynamic contrast-enhanced (DCE) MRI before CRT. A total of 103 imaging features, analyzed using both volume-averaged and voxelized methods, were extracted for each patient. Univariate analyses were performed to evaluate the capability of each individual parameter in predicting pathologic complete response (pCR) or good response (GR) evaluated based on tumor regression grade. Artificial neural network with 4-fold validation technique was further utilized to select the best predictor sets to classify different response groups and the predictive performance was calculated using receiver operating characteristic (ROC) curves.

RESULTS

The conventional volume-averaged analysis could provide an area under ROC curve (AUC) ranging from 0.54 to 0.73 in predicting pCR. While if the models were replaced by voxelized heterogeneity analysis, the prediction accuracy measured by AUC could be improved to 0.71-0.79. Similar results were found for GR prediction. In addition, each subcategory images could generate moderate power in predicting the response, which if combining all information together, the AUC could be further improved to 0.84 for pCR and 0.89 for GR prediction, respectively.

CONCLUSIONS

Through a systematic analysis of multiparametric MR imaging features, we are able to build models with improved predictive value over conventional imaging metrics. The results are encouraging, suggesting the wealth of imaging radiomics should be further explored to help tailoring the treatment into the era of personalized medicine. Clin Cancer Res; 22(21); 5256-64. ©2016 AACR.

Radiological assessment of anal cancer: an overview and update

Anal cancer is uncommon neoplasm with an incidence of 2 new cases per 100,000 per year in the USA, accounting approximately 0.4 % of all tumors and 2.5 % of gastrointestinal malignancies. An early detection of the anal cancer is crucial for the patient management, whereas the diagnosis at an early stage allows conservative management with sphincter sparing, on the contrary a delays in diagnosis might lead to an advance cancer stage at presentation with worst survival. According to National Comprehensive Cancer Network (NCCN) Anal Carcinoma guidelines the patients should be subjected to a careful clinical examination, including a digital rectal examination (DRE), an anoscopic examination, and palpation of inguinal nodes. The guidelines recommended for the assessment of T stage, only a clinical examination, while the role of imaging techniques, as Magnetic Resonance imaging (MRI) is limited to the identification of regional nodes. Instead, the endoanal ultrasound (EAUS) is not recommended. This paper presents an overview and some updates about 3D EAUS and MRI in detection, staging and assessment post therapy of anal cancer patients.

Pre-operative staging of rectal cancer: a review of imaging techniques

INTRODUCTION

The treatment of rectal cancer has diversified in recent years, presenting the clinician and patient with increasingly challenging management decisions. At the heart of this decision-making process are two competing interests; more radical but more morbid treatments which optimize oncological outcome, and less radical treatments which preserve organs and function but may pose a greater risk of disease recurrence.

AREAS COVERED

Imaging plays a vital role informing this decision-making process, both by providing prognostic details about the cancer before the start of treatment and by updating this picture as the cancer responds or fails to respond to treatment. There is a range of available imaging modalities, each with its strengths and weaknesses. Optimizing rectal cancer treatment requires a clear understanding of the important questions that imaging needs to answer and the optimum imaging strategy. Expert Commentary: This article provides an evidence-based review of the available imaging techniques and an expert commentary on the best imaging strategy.

Limited accuracy of DCE-MRI in identification of pathological complete responders after chemoradiotherapy treatment for rectal cancer

OBJECTIVES

To examine whether post-chemoradiotherapy (CRT) DCE-MRI can identify rectal cancer patients with pathologic complete response (pCR).

METHODS

From a rectal cancer surgery database 2007-2014, 61 consecutive patients that met the following inclusion criteria were selected for analysis: (1) stage II/III primary rectal adenocarcinoma; (2) received CRT; (3) underwent surgery (4); underwent rectal DCE-MRI on a 1.5-T MRI scanner. Two experienced radiologists, in consensus, drew regions of interest (ROI) on the sagittal DCE-MRI image in the tumour bed. These were exported from ImageJ to in-house Matlab code for modelling using the Tofts model. K ^trans, K _ep and v _e values were compared to pathological response.

RESULTS

Of the 61 initial patients, 37 had data considered adequate for fitting to obtain perfusion parameters. Among the 13 men and 24 women, median age 53 years, there were 8 pCR (22 %). K ^trans could not distinguish patients with pCR. For patients with 90 % or greater response, mean K ^trans and K _ep values were statistically significant (p = 0.032 and 0.027, respectively). Using a cutoff value of K ^trans = 0.25 min^-1, the AUC was 0.71.

CONCLUSION

K ^trans could be used to identify patients with 90 % or more response to chemoradiotherapy for rectal cancer with an AUC of 0.7.

KEY POINTS

• Chemoradiotherapy for rectal cancer causes decreased blood flow and permeability in the tumour bed. • Lower values of blood flow and permeability correlate with good tumour response. • K ^trans of 0.25min ^-1 best identifies patients with ≥90 % response with AUC 0.71.

MRI for evaluation of treatment response in rectal cancer

MRI plays an increasingly pivotal role in the clinical staging of rectal cancer in the baseline and post-treatment settings. An accurate evaluation of response to neoadjuvant treatment is crucial because of its major influence on patient management and quality of life. However, evaluation of treatment response is challenging for both imaging and clinical assessments owing to treatment-related inflammation and fibrosis. At one end of the spectrum are clinical yT4 rectal cancers, wherein precise post-treatment MRI evaluation of tumour spread is particularly important for avoiding unnecessary exenterative surgery. At the other extreme, for tumours with clinical near-complete response or clinical complete response to neoadjuvant treatment, less invasive treatment may be suitable instead of the standard surgical approach such as, for example, a "Watch and Wait" approach or perhaps local excision. Ideally, the goal of post-treatment MRI evaluation would be to identify these subgroups of patients so that they might be spared unnecessary surgical intervention. It is known that post-chemoradiation therapy restaging using conventional MR sequences is less accurate than baseline staging, particularly in confirming T0 disease, largely owing to the difficulty in distinguishing fibrosis, oedema and normal mucosa from small foci of residual tumour. However, there is a growing utilization of multiparametric MRI, which has superseded other types of evaluations and requires review and periodic re-evaluation. This commentary discusses the current status of multiparametric MRI in the post-treatment setting and the challenges facing imaging in general in the accurate determination of treatment response.

A Novel Prioritization Method in Identifying Recurrent Venous Thromboembolism-Related Genes

Identifying the genes involved in venous thromboembolism (VTE) recurrence is important not only for understanding the pathogenesis but also for discovering the therapeutic targets. We proposed a novel prioritization method called Function-Interaction-Pearson (FIP) by creating gene-disease similarity scores to prioritize candidate genes underling VTE. The scores were calculated by integrating and optimizing three types of resources including gene expression, gene ontology and protein-protein interaction. As a result, 124 out of top 200 prioritized candidate genes had been confirmed in literature, among which there were 34 antithrombotic drug targets. Compared with two well-known gene prioritization tools Endeavour and ToppNet, FIP was shown to have better performance. The approach provides a valuable alternative for drug targets discovery and disease therapy.

Magnetic Resonance Imaging and Other Imaging Modalities in Diagnostic and Tumor Response Evaluation

Functional imaging is emerging as a valuable contributor to the clinical management of patients with rectal cancer. Techniques such as diffusion-weighted magnetic resonance imaging, perfusion imaging, and positron emission tomography can offer meaningful insights into tissue architecture, vascularity, and metabolism. Moreover, new techniques targeting other aspects of tumor biology are now being developed and studied. This study reviews the potential role of functional imaging for the diagnosis, treatment monitoring, and assessment of prognosis in patients with rectal cancer.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

ADVANCES IN KNOWLEDGE

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