Locally advanced rectal cancer: post-chemoradiotherapy ADC histogram analysis for predicting a complete response

Fractional order calculus model-derived histogram metrics for assessing pathological complete response to neoadjuvant chemotherapy in locally advanced rectal cancer

AIM

This study evaluates the value of diffusion fractional order calculus (FROC) model for the assessment of pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) for locally advanced rectal cancer (LARC) by using histogram analysis derived from whole-tumor volumes.

MATERIALS AND METHODS

Ninety-eight patients were prospectively included. Every patient received MRI scans before and after nCRT using a 3.0-Tesla MRI machine. Parameters of the FROC model, including the anomalous diffusion coefficient (D), intravoxel diffusion heterogeneity (β), spatial parameter (μ), and the standard apparent diffusion coefficient (ADC), were calculated. Changes in median values (ΔX-median) and ratio (rΔX-median) were calculated. Receiver operating characteristic (ROC) curves were used for evaluating the diagnostic performance.

RESULTS

Pre-treatmentβ-10th percentile values were significantly lower in the pCR group compared to the non-pCR group (p < 0.001). The Δβ-median showed higher diagnostic accuracy (AUC = 0.870) and sensitivity (76.67 %) for predicting tumor response compared to MRI tumor regression grading (mrTRG) scores (AUC = 0.722; sensitivity = 90.0 %).

DISCUSSION

The use of FROC alongside comprehensive tumor histogram analysis was found to be practical and effective in evaluating the tumor response to nCRT in LARC patients.

Utilizing radiomics for differential diagnosis of inverted papilloma and chronic rhinosinusitis with polyps based on unenhanced CT scans

To evaluate whether radiomics models based on unenhanced paranasal sinuses CT images could be a useful tool for differentiating inverted papilloma (IP) from chronic rhinosinusitis with polyps (CRSwNP). This retrospective study recruited 240 patients with CRSwNP and 106 patients with IP from three centers. 253 patients from Qilu Hospital were randomly divided into the training set (n = 151) and the internal validation set (n = 102) with a ratio of 6:4. 93 patients from the other two centers were used as the external validation set. The patients with the unilateral disease (n = 115) from Qilu Hospital were selected to further develop a subgroup analysis. Lesion segmentation was manually delineated in CT images. Least absolute shrinkage and selection operator algorithm was performed for feature reduction and selection. Decision tree, support vector machine, random forest, and adaptive boosting regressor were employed to establish the differential diagnosis models. 43 radiomic features were selected for modeling. Among the models, RF achieved the best results, with an AUC of 0.998, 0.943, and 0.934 in the training set, the internal validation set, and the external validation set, respectively. In the subgroup analysis, RF achieved an AUC of 0.999 in the training set and 0.963 in the internal validation set. The proposed radiomics models offered a non-invasion and accurate differential approach between IP and CRSwNP and has some significance in guiding clinicians determining the best treatment plans, as well as predicting the prognosis.

Textural Analysis of Magnetic Resonance Images as an Additional Evaluation Tool of Parotid Glands in Sjögren-Primarily Findings

Magnetic Resonance Imaging (MRI) plays a leading role in diagnosing soft tissue pathologies, especially in the head and neck. It is increasingly popular for evaluating salivary gland issues like neoplasms and Sjogren's Syndrome. Advanced MRI methods, including MRI sialography and texture analysis, offer non-invasive alternatives, enhancing MRI's role. This study focused on the relationship between the apparent diffusion coefficient (ADC) and T2-weighted MRI sialography and texture analysis (TA) of parotid glands in children with and without Sjogren's Syndrome (SS). Using 3.0 Tesla MRI with DWI and T2-weighted imaging, expended texture analysis, first-order statistics (FSOs), second-order, and higher-order statistics were conducted. The results showed significant differences in parotid ADC values, with lower values in the SS group, particularly in cases of higher disease activity. Lower kurtosis values were associated with more severe Tonami Scale grades. FSO parameters correlated well with the texture analysis from T2-weighted images, indicating promise in grading parotid gland inflammation. However, further research is needed to understand the impact of variables like binning and region of interest (ROI) size. This study highlights the potential of texture analysis for assessing parotid gland inflammation and emphasizes the need for more investigations in this area.

Improved effects of the b-value for 2000 sec/mm2 DWI on an accurate qualitative and quantitative assessment of rectal cancer

BACKGROUND AND STUDY OBJECTIVES

A higher b-value Diffusion-weighted imaging (DWI) would improve the contrast between cancerous and noncancerous tissue. Apparent diffusion coefficient (ADC)-histogram analysis is a method that can provide statistical data and quantitative information on tumor heterogeneity. This study aimed to compare two high b-values (1000 and 2000 sec/mm2) DWI in tumor detection and diagnostic performance in identifying early-stage tumor rectal cancer.

PATIENTS AND METHODS

This blinded and blinded retrospective study involved 56 patients with rectal cancer and 45 patients. Two radiologists evaluated the qualitative detection parameters and quantitative parameters of the ADC evaluated histogram and compared them between two DWI sequences (b-value for 1000 sec/mm2 and 2000 sec/mm2). The characteristic curves were used to assess diagnostic administration for the ADC histogram in discriminating early-stage tumors.

RESULTS

The b-value for 2000 sec/mm2 DWI significantly improved AUCs, sensitivity, specificity, and precision and decreased false-positive rate for detection compared to the b-value for 1000 sec/mm2 (p < 0.05). The mean and fifth percentile ADC value for stage I using the b-value for 1000 sec/mm2 DWI was significantly higher than stage ≥ II (p = 0.036II and 0.016 respectively), as the well as fifth, 10th, mean ADC of the fifth, 10th, and 25th ADC percentile at b-value for 2000 sec/mm2 (p = 0.031, 0.014, 0.035 and 0.025 respectively). The AUCs of the fifth percentile ADC at b-value for 2000 sec/mm2 DWI in both readers in differentiating the stage Ⅰ tumor were the highest (0.732 and 0.751).

CONCLUSION

The b-value for 2000 sec/mm2 DWI could improve the accurate detection of rectal cancer. The fifth percentile ADC at b-value for 2000 sec/mm2 sec/mm2 DWI was more useful for discriminating early stage than the b-value for 1000 sec/mm2 DWI.

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

PURPOSE

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

The Value of First-Order Features Based on the Apparent Diffusion Coefficient Map in Evaluating the Therapeutic Effect of Low-Intensity Pulsed Ultrasound for Acute Traumatic Brain Injury With a Rat Model

Purpose

In order to evaluate the neuroprotective effect of low-intensity pulsed ultrasound (LIPUS) for acute traumatic brain injury (TBI), we studied the potential of apparent diffusion coefficient (ADC) values and ADC-derived first-order features regarding this problem.

Methods

Forty-five male Sprague Dawley rats (sham group: 15, TBI group: 15, LIPUS treated: 15) were enrolled and underwent magnetic resonance imaging. Scanning layers were acquired using a multi-shot readout segmentation of long variable echo trains (RESOLVE) to decrease distortion. The ultrasound transducer was applied to the designated region in the injured cortical areas using a conical collimator and was filled with an ultrasound coupling gel. Regions of interest were manually delineated in the center of the damaged cortex on the diffusion weighted images (b = 800 s/mm²) layer by layer for the TBI and LIPUS treated groups using the open-source software ITK-SNAP. Before analysis and modeling, the features were normalized using a z-score method, and a logistic regression model with a backward filtering method was employed to perform the modeling. The entire process was completed using the R language.

Results

During the observation time, the ADC values ipsilateral to the trauma in the TBI and LIPUS groups increased rapidly up to 24 h. After statistical analysis, the 10th percentile, 90th percentile, mean, skewness, and uniformity demonstrated a significant difference among three groups. The receiver operating characteristic curve (ROC) analysis shows that the combined LR model exhibited the highest area under the curve value (AUC: 0.96).

Conclusion

The combined LR model of first-order features based on the ADC map can acquire a higher diagnostic performance than each feature only in evaluating the neuroprotective effect of LIPUS for TBI. Models based on first-order features may have potential value in predicting the therapeutic effect of LIPUS in clinical practice in the future.

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

BACKGROUND

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Prediction of overall survival in patients with pancreatic ductal adenocarcinoma: histogram analysis of ADC value and correlation with pathological intratumoral necrosis

BACKGROUND

To evaluate the utility of histogram analysis (HA) of apparent diffusion coefficient (ADC) values to predict the overall survival (OS) in patients with pancreatic ductal adenocarcinoma (PDAC) and to correlate with pathologically evaluated massive intratumoral necrosis (MITN).

MATERIALS AND METHODS

Thirty-nine patients were included in this retrospective study with surgically resected PDAC who underwent preoperative magnetic resonance imaging. Twelve patients received neoadjuvant chemotherapy. HA on the ADC maps were performed to obtain the tumor HA parameters. Using Cox proportional regression analysis adjusted for age, time-dependent receiver-operating-characteristic (ROC) curve analysis, and Kaplan-Meier estimation, we evaluated the association between HA parameters and OS. The association between prognostic factors and pathologically confirmed MITN was assessed by logistic regression analysis.

RESULTS

The median OS was 19.9 months. The kurtosis (P < 0.001), entropy (P = 0.013), and energy (P = 0.04) were significantly associated with OS. The kurtosis had the highest area under the ROC curve (AUC) for predicting 3-year survival (AUC 0.824) among these three parameters. Between the kurtosis and MITN, the logistic regression model revealed a positive correlation (P = 0.045). Lower survival rates occurred in patients with high kurtosis (cutoff value > 2.45) than those with low kurtosis (≤ 2.45) (P < 0.001: 1-year survival rate, 75.2% versus 100%: 3-year survival rate, 14.7% versus 100%).

CONCLUSIONS

HA derived kurtosis obtained from tumor ADC maps might be a potential imaging biomarker for predicting the presence of MITN and OS in patients with PDAC.

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.

The history of magnetic resonance imaging and its reflections in Acta Radiologica

The first reports in Acta Radiologica on magnetic resonance imaging (MRI) were published in 1984, four years after the first commercial MR scanners became available. For the first two years, all MR papers originated from the USA. Nordic contributions started in 1986, and until 2020, authors from 44 different countries have published MR papers in Acta Radiologica. Papers on MRI have constituted, on average, 30%-40% of all published original articles in Acta Radiologica, with a high of 49% in 2019. The MR papers published since 1984 document tremendous progress in several areas such as magnet and coil design, motion compensation techniques, faster image acquisitions, new image contrast, contrast-enhanced MRI, functional MRI, and image analysis. In this historical review, all of these aspects of MRI are discussed and related to Acta Radiologica papers.

Preliminary Study on Predicting Pathological Staging and Immunohistochemical Markers of Rectal Cancer Based on ADC Histogram Analysis

OBJECTIVE

To analyze the correlation between histogram parameters of ADC and pathological staging of rectal cancer and CD31, CD2-40, S-100, and to explore its predictive value.

MATERIALS AND METHODS

MRI findings of 60 patients with surgically and pathologically proved rectal cancer were analyzed retrospectively. Patients were divided into pT1-2, pT3-4, pN0, pN1-2, G1-2 and G3 groups according to TNM staging of UICC tumors (2019) and WHO classification of digestive system tumors (2019). Cases were divided into CD31 (+) and CD31 (-), CD2-40 (+) and CD4-20 (-), S-100 (+) and S-100 (-) groups according to the expression of immunohistochemical markers. The ROI was delineated layer by layer on the ADC images by Firevoxel software, and the histogram parameters were extracted. The histogram parameters (ADC mean, ADC minimum, ADC maximum, ADC mode, ADC quartile), skewness, kurtosis and entropy were compared between each group. The bivariate logistic regression model was used to predict the tumor staging and immunohistochemical results.

RESULTS

1. ADC10th, ADC mean and Entropy were higher than pT3-4, ADC mean was higher than pT1-2, Entropy was lower than pT1-2, ADC10th, ADC25th, ADC50th, ADC mean and ADC mode were lower than pT3-40 (-) in CD2-40 (+) group, and the difference was statistically significant (p < 0.05); 2. The lower area of the curve (AUC) of rectal cancer pT, pN and CD2-40 (+) is 0.952 (0.892-1.000), 0.882 (0.791-0.972), 0.913 (0.840-0.985); 3. In the logistic regression model, higher ADC, Ropy and higher pN stages are independent predictors of tumor pT stages (OR = 1.156, 1.144,111.528); p = 0.045, 0.048, 0.002); higher Ropy and lower pT stages are independent predictors of tumor pN stages in the model (OR = 73.939, 0.024; p = 0.019, 0.001); higher ADC and lower differentiation are independent predictors of tumor CD2-40 stages in the model (ADC = 1.17, 0.048, 0.011); and higher Ropy and lower pT stages are independent predictors of tumor CD2-40 stages in the model (ADC = 1.096, 0.094, 0.044).

CONCLUSION

Histogram analysis based on ADC images has potential value in predicting the pathologic stage and immunohistochemical markers of rectal cancer, and logistic regression model has better diagnostic efficacy than single parameter.

Histogram Analysis of Diffusion-Weighted MR Imaging as a Biomarker to Predict Survival of Surgically Treated Colorectal Cancer Patients

BACKGROUND

Structural abnormality is a well-recognized feature of malignancy. On the other hand, diffusion-weighted MRI (DWI) has been reported as a tool that can reflect tumor biology.

AIMS

The purpose of this study is to apply histogram analysis to DWI to quantify structural abnormality of colorectal cancer, and evaluate its biomarker value.

METHODS

This is a retrospective study of 80 (46 men and 34 women; median age: 68.0 years) colorectal cancer patients who underwent DWI followed by curative surgery at the Chiba University Hospital between 2009 and 2011. Median follow-up time was 62.2 months. Histogram parameters including signal intensity of kurtosis and skewness of the tumor were measured on DWI at b = 1000, and mean apparent diffusion coefficient value (ADC) of the tumor was also measured on ADC map generated by DWIs at b = 0 and 1000. Associations of tumor parameters (kurtosis, skewness, and ADC) with pathological features were analyzed, and these parameters were also compared with overall survival (OS) and relapse-free survival (RFS) using Cox regression and Kaplan-Meier analysis.

RESULTS

ADC of the tumor did not have significant associations with any pathological factors, but kurtosis and skewness of signal intensity in the tumor was significantly different between tumors with distant metastases and those without (4.23 ± 1.31 vs. 3.24 ± 1.32, p = 0.04; 1.09 ± 0.39 vs. 0.57 ± 0.58, p = 0.03). Kurtosis of the tumor was significantly correlated with OS and RFS (p = 0.04, p = 0.03, respectively), and skewness was significantly correlated with OS (p = 0.03) in Cox regression analysis. Higher kurtosis or higher skewness of the tumor was associated with worse OS in Kaplan-Meier analysis (p = 0.01, p = 0.009, log-rank). In subset analysis, there were 50 patients (32 men and 18 women) of lymph node-negative colorectal cancers (≤ stage II); skewness of signal intensity in the tumor was associated with OS using univariate Cox regression analysis (p = 0.04).

CONCLUSIONS

Histogram analysis of DWI can be a prognostic biomarker for colorectal cancer.

Value of Apparent Diffusion Coefficient Histogram Analysis in the Differential Diagnosis of Nasopharyngeal Lymphoma and Nasopharyngeal Carcinoma Based on Readout-Segmented Diffusion-Weighted Imaging

Background

This study aims to explore the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis for differentiating nasopharyngeal lymphoma (NPL) from nasopharyngeal carcinoma (NPC) following readout-segmented echo-planar diffusion-weighted imaging (RESOLVE sequence).

Methods

Thirty-eight patients with NPL and 62 patients with NPC, who received routine head-and-neck MRI and RESOLVE (b-value: 0 and 1,000 s/mm²) examinations, were retrospectively evaluated as derivation cohort (February 2015 to August 2018); another 23 patients were analyzed as validation cohort (September 2018 to December 2019). The RESOLVE data were obtained from the MAGNETOM Skyra 3T MR system (Siemens Healthcare, Erlangen, Germany). Fifteen parameters derived from the whole-lesion histogram analysis (ADC_mean, variance, skewness, kurtosis, ADC₁, ADC₁₀, ADC₂₀, ADC₃₀, ADC₄₀, ADC₅₀, ADC₆₀, ADC₇₀, ADC₈₀, ADC₉₀, and ADC₉₉) were calculated for each patient. Then, statistical analyses were performed between the two groups to determine the statistical significance of each histogram parameter. A receiver operating characteristic curve (ROC) analysis was conducted to assess the diagnostic performance of each histogram parameter for distinguishing NPL from NPC and further tested in the validation cohort; calibration of the selected parameter was tested with Hosmer-Lemeshow test.

Results

NPL exhibited significantly lower ADC_mean, variance, ADC₁, ADC₁₀, ADC₂₀, ADC₃₀, ADC₄₀, ADC₅₀, ADC₆₀, ADC₇₀, ADC₈₀, ADC₉₀ and ADC₉₉, when compared to NPC (all, P < 0.05), while no significant differences were found on skewness and kurtosis. Furthermore, ADC₉₉ revealed the highest diagnostic efficiency, followed by ADC₁₀ and ADC₂₀. Optimal diagnostic performance (AUC = 0.790, sensitivity = 91.9%, and specificity = 63.2%) could be achieved when setting ADC₉₉ = 1,485.0 × 10^-6 mm²/s as the threshold value. The predictive performance was maintained in the validation cohort (AUC = 0.817, sensitivity = 94.6%, and specificity = 56.2%).

Conclusion

Whole-lesion ADC histograms based on RESOLVE are effective in differentiating NPC from NPL.

Value of Intra-Perinodular Textural Transition Features from MRI in Distinguishing Between Benign and Malignant Testicular Lesions

Purpose

To compare the performance of histogram analysis and intra-perinodular textural transition (Ipris) for distinguishing between benign and malignant testicular lesions.

Patients and Methods

This retrospective study included 76 patients with 80 pathologically confirmed testicular lesions (55 malignant, 25 benign). All patients underwent preoperative T2-weighted imaging (T2WI) on a 3.0T MR scanner. All testicular lesions were manually segmented on axial T2WI, and histogram and Ipris features were extracted. Thirty enrolled patients were randomly selected to estimate the robustness of the features. We used intraclass correlation coefficients (ICCs) to evaluate intra- and interobserver agreement of features, independent t-test or Mann–Whitney U-test to compare features between benign and malignant lesions, and receiver operating characteristic curve analysis to evaluate the diagnostic performance of features.

Results

Eighteen histogram features and forty-eight Ipris features were extracted from T2WI of each lesion. Most (60/66) histogram and Ipris features had good robustness (ICC of both intra- and interobserver variabilities >0.6). Three histogram and nine Ipris features were significantly different between the benign and malignant groups. The area under the curve values for Energy, TotalEnergy, and Ipris_shell1_id_std were 0.807, 0.808, and 0.708, respectively, which were relatively higher than those of other features.

Conclusion

Ipris features may be useful for identifying benign and malignant testicular tumors but have no significant advantage over conventional histogram features.

Correlation of the tumour-stroma ratio with diffusion weighted MRI in rectal cancer

OBJECTIVE

This study evaluated the correlation between intratumoural stroma proportion, expressed as tumour-stroma ratio (TSR), and apparent diffusion coefficient (ADC) values in patients with rectal cancer.

METHODS

This multicentre retrospective study included all consecutive patients with rectal cancer, diagnostically confirmed by biopsy and MRI. The training cohort (LUMC, Netherlands) included 33 patients and the validation cohort (VHIO, Spain) 69 patients. Two observers measured the mean and minimum ADCs based on single-slice and whole-volume segmentations. The TSR was determined on diagnostic haematoxylin & eosin stained slides of rectal tumour biopsies. The correlation between TSR and ADC was assessed by Spearman correlation (r_s).

RESULTS

The ADC values between stroma-low and stroma-high tumours were not significantly different. Intra-class correlation (ICC) demonstrated a good level of agreement for the ADC measurements, ranging from 0.84-0.86 for single slice and 0.86-0.90 for the whole-volume protocol. No correlation was observed between the TSR and ADC values, with ADC_meanr_s= -0.162 (p= 0.38) and ADC_minr_s= 0.041 (p= 0.82) for the single-slice and r_s= -0.108 (p= 0.55) and r_s= 0.019 (p= 0.92) for the whole-volume measurements in the training cohort, respectively. Results from the validation cohort were consistent; ADC_meanr_s= -0.022 (p= 0.86) and ADC_minr_s = 0.049 (p= 0.69) for the single-slice and r_s= -0.064 (p= 0.59) and r_s= -0.063 (p= 0.61) for the whole-volume measurements.

CONCLUSIONS

Reproducibility of ADC values is good. Despite positive reports on the correlation between TSR and ADC values in other tumours, this could not be confirmed for rectal cancer.

Multiparametric MRI in rectal cancer

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

Whole-Volume ADC Histogram Analysis in Parotid Glands to Identify Patients with Sjögren's Syndrome

At present, no gold standard for diagnosing Sjögren’s syndrome (SS) is available in clinical practice. The 2002 American–European Consensus Group classification criteria are used to diagnose SS. Clinically, it is challenging to distinguish patients with SS from suspected patients undergoing different therapies. A total of 52 patients with SS and 24 patients suspected of having the disease prospectively underwent 3.0-T magnetic resonance (MR) scanning, including diffusion-weighted imaging (b = 0 and 1000 s/mm²). The whole-volume apparent diffusion coefficient (ADC) histogram analysis generated ADC_mean, skewness, kurtosis, and entropy values from bilateral parotid glands. Continuous variables were compared using an independent two-sample t test, and categorical variable compared using the Fisher’s test between the two groups. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of the indexes. Fisher’s tests demonstrated that some clinical indexes and MR morphology grades differed significantly between patients with SS and patients suspected of having the disease (all P ≤ 0.001). The parotid entropy value of patients with SS was significantly higher than that of patients suspected of having the disease (P < 0.001). Among MR parameters, entropy combined with kurtosis performed the best in differentiating patients with SS from those suspected of having SS (area under the ROC curve = 0.955). A whole-volume ADC histogram analysis might provide a series of parameters that reflect tissue characteristics.

Diffusion-weighted imaging in rectal cancer: current applications and future perspectives

This review summarizes current applications and clinical utility of diffusion-weighted imaging (DWI) for rectal cancer and in addition provides a brief overview of more recent developments (including intravoxel incoherent motion imaging, diffusion kurtosis imaging, and novel postprocessing tools) that are still in more early stages of research. More than 140 papers have been published in the last decade, during which period the use of DWI have slowly moved from mainly qualitative (visual) image interpretation to increasingly advanced methods of quantitative analysis. So far, the largest body of evidence exists for assessment of tumour response to neoadjuvant treatment. In this setting, particularly the benefit of DWI for visual assessment of residual tumour in post-radiation fibrosis has been established and is now increasingly adopted in clinics. Quantitative DWI analysis (mainly the apparent diffusion coefficient) has potential, both for response prediction as well as for tumour prognostication, but protocols require standardization and results need to be prospectively confirmed on larger scale. The role of DWI for further clinical tumour and nodal staging is less well-defined, although there could be a benefit for DWI to help detect lymph nodes. Novel methods of DWI analysis and post-processing are still being developed and optimized; the clinical potential of these tools remains to be established in the upcoming years.

Multimodal Imaging of Pathologic Response to Chemoradiation in Esophageal Cancer

PURPOSE

To examine the value of early changes in quantitative diffusion-weighted imaging and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) for discriminating complete pathologic response (pCR) to chemoradiation in esophageal cancer.

METHODS AND MATERIALS

Twenty esophageal cancer patients treated with chemoradiation followed by surgery were prospectively enrolled. Patients underwent magnetic resonance imaging and FDG-PET/CT scans at baseline, interim (2 weeks after chemoradiation start), and first follow-up. On the basis of pathologic findings at surgery, patients were categorized into tumor regression groups (TRG1, TRG2, and TRG3+). Distributions of summary statistics in apparent diffusion coefficient (ADC) and FDG-PET at baseline and relative changes at interim and follow-up scans were compared between pCR/TRG1 and non-pCR/TRG2+ groups and across readers. Receiver operating characteristics were evaluated for summary measures to characterize discrimination of pCR from non-pCR.

RESULTS

Relative changes in tumor volume ADC (ΔADC) mean and 25th and 10th percentiles from baseline to interim were able to completely discriminate (area under the curve = 1, P < .0011) between pCR and non-pCR (thresholds = 27.7%, 29.2%, and 32.1%, respectively) and were found to have high interreader reliability (95% limits of agreement of 1.001, 0.944, and 0.940, respectively). Relative change in total lesion glycolysis (TLG) from baseline to interim was significantly different among pCR and non-pCR groups (P=.0117) and yielded an area under the curve of 0.947 (95% confidence interval 0.8505-1.043). An optimal threshold of 59% decrease in TLG provided optimal sensitivity (specificity) of 1.000 (0.867). Changes in ADC summary measures were negatively correlated with that of TLG (Spearman, -0.495, P=.027).

CONCLUSIONS

Quantitative volume ΔADC and TLG during treatment may serve as early imaging biomarkers for discriminating pathologic response to chemoradiation in esophageal cancer. Validation of these data in larger, prospective, multicenter studies is essential.

Whole-volume ADC Histogram and Texture Analyses of Parotid Glands as an Image Biomarker in Evaluating Disease Activity of Primary Sjögren's Syndrome

Diffusion weighted imaging (DWI) has proven to be sensitive for detecting early injury to the parotid gland in pSS (primary Sjögren’s syndrome). Here, we explored the application of ADC histogram and texture analyses for evaluating the disease activity of pSS. A total of 55 patients with pSS who met the classification criteria of the 2002 AECG criteria prospectively underwent 3.0-T magnetic resonance imaging (MRI) including DWI (b = 0 and 1000 s/mm²). According to the ESSDAI score, 35 patients were categorized into the low-activity group (ESSDAI < 5) and 20 into the moderate-high-activity group (ESSDAI ≥ 5). Via analysis of the whole-volume ADC histogram, the ADC_mean, skewness, kurtosis, and entropy values of the bilateral parotid glands were determined. Multivariate analysis was used to identify independent risk factors for predicting disease activity. The diagnostic performance of the indexes was evaluated via receiver operating characteristic (ROC) analysis. ROC analysis showed that the anti-SSB, lip biopsy, MRI morphology, ADC, ADC_mean, and entropy values were able to categorize the disease into two groups, particularly the entropy values. The multivariate model, which included anti-SSB, MRI morphology and entropy, had an area under the ROC curve of 0.923 (P < 0.001). The parotid entropy value distinguished disease activity in patients with pSS, especially combined with anti-SSB and MRI morphology.

MRI-Based Apparent Diffusion Coefficient for Predicting Pathologic Response of Rectal Cancer After Neoadjuvant Therapy: Systematic Review and Meta-Analysis

OBJECTIVE

The purpose of this study was to assess the use of apparent diffusion coefficient (ADC) during DWI for predicting complete pathologic response of rectal cancer after neoadjuvant therapy.

MATERIALS AND METHODS

A systematic review of available literature was conducted to retrieve studies focused on the identification of complete pathologic response of locally advanced rectal cancer after neoadjuvant chemoradiation, through the assessment of ADC evaluated before, after, or both before and after treatment, as well as in terms of the difference between pretreatment and posttreatment ADC. Pooled mean pretreatment ADC, posttreatment ADC, and Δ-ADC (calculated as posttreatment ADC minus pretreatment ADC divided by pretreatment ADC and multiplied by 100) in complete responders versus incomplete responders were calculated. For each parameter, we also pooled sensitivity and specificity and calculated the area under the summary ROC curve.

RESULTS

We found 10 prospective and eight retrospective studies. Overall, pathologic complete response was observed in 22.2% of patients. Pooled mean pretreatment ADC in complete responders was 0.84 × 10^-3 mm²/s versus 0.89 × 10^-3 mm²/s in incomplete responders (p = 0.33). Posttreatment ADC values were 1.51 × 10^-3 mm²/s and 1.29 × 10^-3 mm²/s, in complete and incomplete responders, respectively (p = 0.00001). The Δ-ADC percentages were also significantly higher in complete responders than in incomplete responders (59.7% vs 29.7%, respectively, p = 0.016). Pooled sensitivity, specificity, and AUC were 0.743, 0.755, and 0.841 for pretreatment ADC; 0.800, 0.737, and 0.782 for posttreatment ADC; and 0.832, 0.806, and 0.895 for Δ-ADC.

CONCLUSION

Use of ADC during DWI is a promising technique for assessment of results of neoadjuvant treatment of rectal cancer.

Histogram Analysis of Perfusion Parameters from Dynamic Contrast-Enhanced MR Imaging with Tumor Characteristics and Therapeutic Response in Locally Advanced Rectal Cancer

Purpose

To explore the role of histogram analysis of perfusion parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based on entire tumor volume in discriminating tumor characteristics and predicting therapeutic response in rectal cancer.

Materials and Methods

Thirty-seven DCE-MRIs of locally advanced rectal cancer patients who received chemoradiation therapy (CRT) before surgery were analyzed by pharmacokinetic model for quantification and histogram analysis of perfusion parameters. The results were correlated with tumor characteristics including EGFR expression, KRAS mutation, and CRT response based on the pathologic tumor regression grade (TRG).

Results

The area under the contrast agent concentration-time curve (AUC) skewness was significantly lower in patients with node metastasis. The v_p histogram parameters were significantly higher in group with perineural invasion (PNI). The receiver operating characteristics (ROC) curve analyses showed that mode v_p revealed the best diagnostic performance of PNI. The values of K^trans and k_ep were significantly higher in the group with KRAS mutation. ROC curve analyses showed that mean and mode K^trans demonstrated excellent diagnostic performance of KRAS mutation. DCE-MRI parameters did not demonstrate statistical significance in correlating with TRG.

Conclusion

These preliminary results suggest that a larger proportion of higher AUC skewness was present in LN metastasis group and a higher v_p histogram value was present in rectal cancer with PNI. In addition, K^trans and k_ep histogram parameters showed difference according to the KRAS mutation, demonstrating the utility of the histogram of perfusion parameters derived from DCE-MRI as potential imaging biomarkers of tumor characteristics and genetic features.

Histogram analysis of apparent diffusion coefficient from whole-body diffusion-weighted MRI to predict early response to chemotherapy in patients with metastatic colorectal cancer: preliminary results

AIM

To evaluate apparent diffusion coefficient (ADC) histogram analysis parameters, acquired from whole-body diffusion-weighted magnetic resonance imaging (DW-MRI), as very early predictors of response to chemotherapy in patients with metastatic colorectal cancer (mCRC).

MATERIALS AND METHODS

This was a single-institution prospective study, approved by the West Midlands-South Birmingham research ethics committee. All patients gave fully informed consent prior to imaging. Sixteen patients with histologically confirmed mCRC were enrolled to the study and 11 were successfully scanned with whole-body DW-MRI before (baseline) and 10.8±2.7 days after commencing chemotherapy (follow-up). Therapy response was assessed by RECIST 1.1. Mean ADC and histogram parameters (skewness, kurtosis, 25^th, 50^th, and 75^th percentiles) were compared between progressors and non-progressors at baseline and follow-up. Receiver operating characteristics (ROC) analysis was performed for the statistically significant parameters. Data from metastases were also compared to normative tissue data acquired from healthy volunteers.

RESULTS

Three patients had progressive disease (progressors) and eight had partial response/stable disease (non-progressors). Mean, 25^th, 50^th, and 75^th percentiles were significantly lower for progressors at baseline (p=0.012, 0.012, 0.012 and 0.025 respectively) with areas under the ROC curves (AUC)=0.58, 0.50, 0.58 and 0.63, respectively. Skewness and kurtosis were significantly lower for non-progressors at follow-up (p=0.001 and 0.003 respectively) with AUC=0.67 and 0.79 respectively.

CONCLUSION

ADC histogram analysis shows potential in discriminating progressive from non-progressive disease in patients with mCRC, who underwent whole-body DW-MRI. The technique can potentially be tested as a response assessment methodology in larger trials.

Morphologic predictors of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer

Purpose

To evaluate the value of morphological parameters that can be obtained conveniently by MRI for predicting pathologically complete response (pCR) in patients with rectal cancer.

Materials and Methods

A cohort of 101 patients was examined using MRI before and after Neoadjuvant chemoradiotherapy (nCRT). Morphological parameters including maximum tumor area (MTA), maximum tumor length (MTL) and maximum tumor thickness (MTT), as well as cylindrical approximated tumor volume (CATV), distance to anal verge (DTA), and the reduction rates were evaluated by two experienced readers independently.

Results

Post-nCRT MTA and MTL, reduction rates and pre-nCRT DTA were proved to be significantly different between pCR and non-pCR with the AUCs of 0.672-0.853. The sensitivity and specificity for assessing pCR were 61.1-89.9% and 59.0-80.7% respectively. No significant correlation between pre-nCRT size measurements and pCR was obtained.

Conclusion

The convenient morphological measurements may be useful for predicting pCR with moderate sensitivity and specificity. Combining these predictors with the aim of building diagnostic model should be explored.

Diffusion weighted imaging in patients with rectal cancer: Comparison between Gaussian and non-Gaussian models

Purpose

The purpose of this study was to compare the performance of four diffusion models, including mono and bi-exponential both Gaussian and non-Gaussian models, in diffusion weighted imaging of rectal cancer.

Material and methods

Nineteen patients with rectal adenocarcinoma underwent MRI examination of the rectum before chemoradiation therapy including a 7 b-value diffusion sequence (0, 25, 50, 100, 500, 1000 and 2000 s/mm²) at a 1.5T scanner. Four different diffusion models including mono- and bi-exponential Gaussian (MG and BG) and non-Gaussian (MNG and BNG) were applied on whole tumor volumes of interest. Two different statistical criteria were recruited to assess their fitting performance, including the adjusted-R² and Root Mean Square Error (RMSE). To decide which model better characterizes rectal cancer, model selection was relied on Akaike Information Criteria (AIC) and F-ratio.

Results

All candidate models achieved a good fitting performance with the two most complex models, the BG and the BNG, exhibiting the best fitting performance. However, both criteria for model selection indicated that the MG model performed better than any other model. In particular, using AIC Weights and F-ratio, the pixel-based analysis demonstrated that tumor areas better described by the simplest MG model in an average area of 53% and 33%, respectively. Non-Gaussian behavior was illustrated in an average area of 37% according to the F-ratio, and 7% using AIC Weights. However, the distributions of the pixels best fitted by each of the four models suggest that MG failed to perform better than any other model in all patients, and the overall tumor area.

Conclusion

No single diffusion model evaluated herein could accurately describe rectal tumours. These findings probably can be explained on the basis of increased tumour heterogeneity, where areas with high vascularity could be fitted better with bi-exponential models, and areas with necrosis would mostly follow mono-exponential behavior.

Intravoxel incoherent motion diffusion-weighted imaging for discriminating the pathological response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer

To investigate the usefulness of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in discriminating the pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC), 42 patients underwent preoperative IVIM-DWI before (pre-nCRT) and after nCRT (post-nCRT). The values of pre-nCRT and post-nCRT IVIM-DWI parameters (ADC, D, D* and f), together with the percentage changes (∆% parametric value) induced by nCRT, were compared between the pCR (tumour regression grade [TRG] 4) and non-pCR (TRG 0, 1, 2 or 3) groups and between the GR (TRG 3 or 4) and PR (TRG 0, 1 or 2) groups based on the Dworak TRG system. After nCRT, the ADC and D values for LARC increased significantly (all P < 0.05). The TRG score revealed a positive correlation with pref (r = 0.357, P = 0.020), postD (r = 0.551, P < 0.001) and Δ%D (r = 0.605, P < 0.001). The pCR group (n = 10) had higher preD*, pref, postD, ∆%ADC and ∆%D values than the non-pCR group (n = 32) (all P < 0.05). The GR group (n = 15) exhibited higher postD, ∆%ADC and ∆%D values than the PR group (n = 27) (all P < 0.05). Based on ROC analysis, ∆%D had a higher area under the curve value than ∆%ADC (P = 0.009) in discriminating the pCR from non-pCR groups. In conclusion, IVIM-DWI may be helpful in identifying the pCR to nCRT for LARC and is more accurate than traditional DWI.

Measuring the apparent diffusion coefficient in primary rectal tumors: is there a benefit in performing histogram analyses?

Purpose

The apparent diffusion coefficient (ADC) is a potential prognostic imaging marker in rectal cancer. Typically, mean ADC values are used, derived from precise manual whole-volume tumor delineations by experts. The aim was first to explore whether non-precise circular delineation combined with histogram analysis can be a less cumbersome alternative to acquire similar ADC measurements and second to explore whether histogram analyses provide additional prognostic information.

Methods

Thirty-seven patients who underwent a primary staging MRI including diffusion-weighted imaging (DWI; b0, 25, 50, 100, 500, 1000; 1.5 T) were included. Volumes-of-interest (VOIs) were drawn on b1000-DWI: (a) precise delineation, manually tracing tumor boundaries (2 expert readers), and (b) non-precise delineation, drawing circular VOIs with a wide margin around the tumor (2 non-experts). Mean ADC and histogram metrics (mean, min, max, median, SD, skewness, kurtosis, 5th–95th percentiles) were derived from the VOIs and delineation time was recorded. Measurements were compared between the two methods and correlated with prognostic outcome parameters.

Results

Median delineation time reduced from 47–165 s (precise) to 21–43 s (non-precise). The 45th percentile of the non-precise delineation showed the best correlation with the mean ADC from the precise delineation as the reference standard (ICC 0.71–0.75). None of the mean ADC or histogram parameters showed significant prognostic value; only the total tumor volume (VOI) was significantly larger in patients with positive clinical N stage and mesorectal fascia involvement.

Conclusion

When performing non-precise tumor delineation, histogram analysis (in specific 45th ADC percentile) may be used as an alternative to obtain similar ADC values as with precise whole tumor delineation. Histogram analyses are not beneficial to obtain additional prognostic information.

Investigation of volumetric apparent diffusion coefficient histogram analysis for assessing complete response and clinical outcomes following pre-operative chemoradiation treatment for rectal carcinoma

PURPOSE

To investigate the relationship of pre-treatment volumetric apparent diffusion coefficient (ADC) histogram parameters with post-operative histopathologic treatment response and clinical outcomes following pre-operative chemoradiation treatment (CRT) in rectal cancer.

MATERIALS AND METHODS

In a Health Insurance Portability and Accountability Act compliant retrospective study, 78 rectal cancer patients treated with pre-operative CRT and rectal MRI were included. MR imaging analysis was performed using OncoTREAT (software tool). Multiple volumetric ADC histogram parameters (voxel distribution across ADC ranges, kurtosis, and skewness) were assessed. Correlation was made to post-operative pathological complete response, clinical, or radiological evidence of disease progression using the Mann-Whitney test.

RESULTS

Post CRT, 8 patients showed pathologic complete response and 13 patients showed distant disease progression. Pre-treatment mean ADC was 1.2 × 10^-3 mm²/s (range 0.3-1.99 × 10^-3 mm²/s). Mean kurtosis measured was 0.56 (range -1 to 6; SD 1.36). Mean skewness was 0.3 (range -1 to 2; SD 0.69). Skewness had significant correlation (p value = 0.006) with disease progression. The mean rectal tumor volume was 24cc (range 1cc-134cc). Pre-treatment MRI tumor volume showed significant correlation (p value = 0.013) with pathologic complete response. Mean ADC and percentage voxels distribution against ADC ranges had no significant correlation with treatment response or disease outcomes.

CONCLUSION

Volumetric ADC histogram analysis of pre-CRT rectal cancer MRI appears promising for prediction of post-CRT complete response and disease progression.

Utility of whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs)

PURPOSE

To evaluate whole-lesion ADC histogram metrics for assessing the malignant potential of pancreatic intraductal papillary mucinous neoplasms (IPMNs), including in comparison with conventional MRI features.

METHODS

Eighteen branch-duct IPMNs underwent MRI with DWI prior to resection (n = 16) or FNA (n = 2). A blinded radiologist placed 3D volumes-of-interest on the entire IPMN on the ADC map, from which whole-lesion histogram metrics were generated. The reader also assessed IPMN size, mural nodularity, and adjacent main-duct dilation. Benign (low-to-intermediate grade dysplasia; n = 10) and malignant (high-grade dysplasia or invasive adenocarcinoma; n = 8) IPMNs were compared.

RESULTS

Whole-lesion ADC histogram metrics demonstrating significant differences between benign and malignant IPMNs were: entropy (5.1 ± 0.2 vs. 5.4 ± 0.2; p = 0.01, AUC = 86%); mean of the bottom 10th percentile (2.2 ± 0.4 vs. 1.6 ± 0.7; p = 0.03; AUC = 81%); and mean of the 10-25th percentile (2.8 ± 0.4 vs. 2.3 ± 0.6; p = 0.04; AUC = 79%). The overall mean ADC, skewness, and kurtosis were not significantly different between groups (p ≥ 0.06; AUC = 50-78%). For entropy (highest performing histogram metric), an optimal threshold of >5.3 achieved a sensitivity of 100%, a specificity of 70%, and an accuracy of 83% for predicting malignancy. No significant difference (p = 0.18-0.64) was observed between benign and malignant IPMNs for cyst size ≥3 cm, adjacent main-duct dilatation, or mural nodule. At multivariable analysis of entropy in combination with all other ADC histogram and conventional MRI features, entropy was the only significant independent predictor of malignancy (p = 0.004).

CONCLUSION

Although requiring larger studies, ADC entropy obtained from 3D whole-lesion histogram analysis may serve as a biomarker for identifying the malignant potential of IPMNs, independent of conventional MRI features.

Utility of histogram analysis of ADC maps for differentiating orbital tumors

PURPOSE

We aimed to evaluate the role of histogram analysis of apparent diffusion coefficient (ADC) maps for differentiating benign and malignant orbital tumors.

METHODS

Fifty-two patients with orbital tumors were enrolled from March 2013 to November 2014. Pretreatment diffusion-weighted imaging was performed on a 3T magnetic resonance scanner with b factors of 0 and 800 s/mm2, and the corresponding ADC maps were generated. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including ADCmean, ADCmedian, standard deviation (SD), skewness, kurtosis, quartile, ADC10, ADC25, ADC75, and ADC90. Histogram parameter differences between benign and malignant orbital tumors were compared. The diagnostic value of each significant parameter in predicting malignant tumors was established.

RESULTS

Age, ADCmean, ADCmedian, quartile, kurtosis, ADC10, ADC25, ADC75, and ADC90 parameters were significantly different between benign and malignant orbital tumor groups, while gender, location, SD, and skewness were not significantly different. The best diagnostic performance in predicting malignant orbital tumors was achieved at the threshold of ADC10=0.990 (AUC, 0.997; sensitivity, 96.2%; specificity, 100%).

CONCLUSION

Histogram analysis of ADC maps holds promise for differentiating benign and malignant orbital tumors. ADC10 has the potential to be the most significant parameter for predicting malignant orbital tumors.

The value of diffusion kurtosis magnetic resonance imaging for assessing treatment response of neoadjuvant chemoradiotherapy in locally advanced rectal cancer

OBJECTIVES

To evaluate the feasibility and value of diffusion kurtosis (DK) imaging in assessing treatment response to neoadjuvant chemoradiotherapy (CRT) in patients with locally advanced rectal cancer (LARC).

METHODS

Forty-one patients were included. All patients underwent pre- and post-CRT DCE-MRI on a 3.0-Tesla MRI scanner. Imaging indices (D _app , K _app and ADC values) were measured. Change value (∆X) and change ratio (r∆X) were calculated. Pathological tumour regression grade scores (Mandard) were the standard reference (good responders: pTRG 1-2; poor responders: pTRG 3-5). Diagnostic performance was compared using ROC analysis.

RESULTS

For the pre-CRT measurements, pre-D _app-10th was significantly lower in the good responder group than that of the poor responder group (p = 0.036). For assessing treatment response to neoadjuvant CRT, pre-D _app-10th resulted in AUCs of 0.753 (p = 0.036) with a sensitivity of 66.67 % and a specificity of 77.78 %. The r∆D _app had a relatively high AUC (0.859) and high sensitivity (100 %) compared with other image indices.

CONCLUSIONS

DKI is feasible for selecting good responders for neoadjuvant CRT for LARC.

KEY POINTS

• LARC responded well after neoadjuvant chemoradiotherapy with lower pre-D _app-10th . • LARC responded well with greater increases in mean ADC and D _app . • The change ratio of D _app (r∆D _app ) had a relatively better diagnostic performance.

Diffusion-weighted magnetic resonance imaging in colorectal cancer

Magnetic resonance imaging (MRI) plays now a major role in patients with colorectal cancer regarding tumor staging, surgical planning, therapeutic decision, assessment of tumor response to chemoradiotherapy and surveillance of rectal cancer, and detection and characterization of liver or peritoneal metastasis of colorectal cancers. Diffusion-weighted MRI (DW-MRI) is a functional imaging tool that is now part of the standard MRI protocol for the investigation of patients with colorectal cancer. DW-MRI reflects micro-displacements of water molecules in tissues and conveys high degrees of accuracy to discriminate between benign and malignant colorectal conditions. Thus, in addition to morphological imaging, DW-MRI has an important role to accurately detect colorectal neoplasms and peritoneal implants, to differentiate benign focal liver lesions from metastases and to detect tumor relapse within fibrotic changes. This review provides a comprehensive overview of basic principles, clinical applications and future trends of DW-MRI in colorectal cancers.

Assessment of histological differentiation in gastric cancers using whole-volume histogram analysis of apparent diffusion coefficient maps

PURPOSE

To investigate the efficacy of histogram analysis of the entire tumor volume in apparent diffusion coefficient (ADC) maps for differentiating between histological grades in gastric cancer.

MATERIALS AND METHODS

Seventy-eight patients with gastric cancer were enrolled in a retrospective 3.0T magnetic resonance imaging (MRI) study. ADC maps were obtained at two different b values (0 and 1000 sec/mm² ) for each patient. Tumors were delineated on each slice of the ADC maps, and a histogram for the entire tumor volume was subsequently generated. A series of histogram parameters (eg, skew and kurtosis) were calculated and correlated with the histological grade of the surgical specimen. The diagnostic performance of each parameter for distinguishing poorly from moderately well-differentiated gastric cancers was assessed by using the area under the receiver operating characteristic curve (AUC).

RESULTS

There were significant differences in the 5^th , 10^th , 25^th , and 50^th percentiles, skew, and kurtosis between poorly and well-differentiated gastric cancers (P < 0.05). There were correlations between the degrees of differentiation and histogram parameters, including the 10^th percentile, skew, kurtosis, and max frequency; the correlation coefficients were 0.273, -0.361, -0.339, and -0.370, respectively. Among all the histogram parameters, the max frequency had the largest AUC value, which was 0.675.

CONCLUSION

Histogram analysis of the ADC maps on the basis of the entire tumor volume can be useful in differentiating between histological grades for gastric cancer.

LEVEL OF EVIDENCE

4 J. Magn. Reson. Imaging 2017;45:440-449.

Advanced imaging of colorectal cancer: From anatomy to molecular imaging

Imaging techniques play a key role in the management of patients with colorectal cancer. The introduction of new advanced anatomical, functional, and molecular imaging techniques may improve the assessment of diagnosis, prognosis, planning therapy, and assessment of response to treatment of these patients. Functional and molecular imaging techniques in clinical practice may allow the assessment of tumour-specific characteristics and tumour heterogeneity. This paper will review recent developments in imaging technologies and the evolving roles for these techniques in colorectal cancer.

TEACHING POINTS

• Imaging techniques play a key role in the management of patients with colorectal cancer. • Advanced imaging techniques improve the evaluation of these patients. • Functional and molecular imaging allows assessment of tumour hallmarks and tumour heterogeneity.

Apparent Diffusion Coefficient Predicts Pathology Complete Response of Rectal Cancer Treated with Neoadjuvant Chemoradiotherapy

Objective

To evaluate the predictive value of the apparent diffusion coefficient (ADC) for pathologic complete response (pCR) to neoadjuvant chemoradiotherapy (NCRT) in locally advanced rectal cancer.

Methods

A total of 265 patients with rectal adenocarcinoma, whole Diffusion-Weighted MRI (DWI-MRI) images, clinically stage II to III (cT3-4 and/or cN+) and treated with NCRT followed by TME were screened. Fifty patients with pCR and another 50 patients without pCR with similar clinical charcacters and treatment regimens were selected for statistical analysis. All the patients’ pre-CRT and post-CRT average ADC values were calculated from the coefficient maps created by DWI-MRI and recorded independently. The difference in the ADC values between the pCR and non-pCR was analyzed by the Mann-Whitney U test. The cut-off ADC value of the receiver operating characteristic (ROC) curve with pCR was then established.

Results

The mean pre- and post-ADC values in all patients, and in pCR patients and non-pCR patients were 0.879±0.06 and 1.383±0.11, 0.859±0.04 and 1.440±0.10, 0.899±0.07 and 1.325±0.09 (×10^-3mm²/s), respectively. The difference between the pre- and post-ADC values in all patients, pCR patients, and non-pCR patients were considered to be statistically significant. The pre-ADC value was significantly lower in the pCR patients than in the non-pCR patients (p = 0.003), whereas the post-ADC values were significantly higher in the pCR patients than in the non-pCR patients. The percentage increase of the ADC value (ΔADC%) in the pCR and non-pCR patients were 68% and 48% respectively (p<0.001). The ROC curves of the cut-off value of the pre-CRT patient ADC value was 0.866×10^-3mm²/s. The AUC, sensitivity, specificity, PPV, NPV, and accuracy of diagnosing pCR were 0.670 (95% CI 0.563–0.777), 0.600, 0.640, 60%, 60%, and 60%, respectively. The cut-off value of ΔADC% was 58%. The corresponding AUC, sensitivity, specificity, PPV, NPV, and accuracy of diagnosing pCR were 0.856 (95% CI 0.783–0.930), 0.800, 0.760, 76.9%, 79.2%, and 78%, respectively.

Conclusions

DWI-MRI technology can be efficient for predicting pCR for LARC after NCRT. Although the mean pre-CRT ADC value and the ΔADC% are moderate predictors for pCR, the latter would be more accurate.

Radiological indeterminate vestibular schwannoma and meningioma in cerebellopontine angle area: differentiating using whole-tumor histogram analysis of apparent diffusion coefficient

PURPOSE

To assess the role of whole-tumor histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating radiological indeterminate vestibular schwannoma (VS) from meningioma in cerebellopontine angle (CPA).

MATERIALS AND METHODS

Diffusion-weighted (DW) images (b = 0 and 1000 s/mm²) of pathologically confirmed and radiological indeterminate CPA meningioma (CPAM) (n = 27) and VS (n = 12) were retrospectively collected and processed with mono-exponential model. Whole-tumor regions of interest were drawn on all slices of the ADC maps to obtain histogram parameters, including the mean ADC (ADC_mean), median ADC (ADC_median), 10th/25th/75th/90th percentile ADC (ADC₁₀, ADC₂₅, ADC₇₅ and ADC₉₀), skewness and kurtosis. The differences of ADC histogram parameters between CPAM and VS were compared using unpaired t-test. Multiple receiver operating characteristic (ROC) curves analysis was used to determine and compare the diagnostic value of each significant parameter.

RESULTS

Significant differences were found on the ADC_mean, ADC_median, ADC₁₀, ADC₂₅, ADC₇₅ and ADC₉₀ between CPAM and VS (all p values < 0.001), while no significant difference was found on kurtosis (p = 0.562) and skewness (p = 0.047). ROC curves analysis revealed, a cut-off value of 1.126 × 10^-3 mm²/s for the ADC₉₀ value generated highest area under curves (AUC) for differentiating CPAM from VS (AUC, 0.975; sensitivity, 100%; specificity, 88.9%).

CONCLUSIONS

Histogram analysis of ADC maps based on whole tumor can be a useful tool for differentiating radiological indeterminate CPAM from VS. The ADC₉₀ value was the most promising parameter for differentiating these two entities.

Orbital Indeterminate Lesions in Adults: Combined Magnetic Resonance Morphometry and Histogram Analysis of Apparent Diffusion Coefficient Maps for Predicting Malignancy

RATIONALE AND OBJECTIVES

The aim of this study was to evaluate the added value of histogram analysis of apparent diffusion coefficient (ADC) maps in differentiating indeterminate orbital malignant tumors from benign tumors, compared to using magnetic resonance (MR) morphological features alone.

MATERIALS AND METHODS

We retrospectively evaluated 54 patients with orbital tumors from March 2013 to February 2015. All the patients were assessed by both routine MR and diffusion-weighted imaging, and divided into benign group and malignant group. Routine MR imaging features and histogram parameters derived from ADC maps, including mean ADC (ADCmean), median ADC (ADCmedian), standard deviation, skewness, kurtosis, and 10th and 90th percentiles of ADC (ADC10 and ADC90), were compared between two groups. Univariate and multivariate logistic regression analyses were used to identify the most valuable variables in predicting malignancy. Receiver operating characteristic (ROC) curve analysis was used to determine the diagnostic value of significant variables.

RESULTS

Multivariate logistic regression analysis indicated that two or more quadrants involved, iso-intense on T2-weighted imaging (T2WI), and ADC10 were significant predictors for orbital malignancy. By using model 2 (iso-intense on T2WI + two or more quadrants involved + ADC10 < 0.990) as the criterion, higher AUC and specificity could be achieved than by using model 1 (iso-intense on T2WI + two or more quadrants involved) alone, (model 2 vs model 1; area under curve (AUC), 0.827 vs 0.793; sensitivity, 65.4% vs 69.2%; specificity, 100% vs 89.3%).

CONCLUSIONS

Iso-intense on T2WI, two or more quadrants involved, and ADC10 are risk factors for orbital malignancy. Histogram analysis of ADC map might provide added value in predicting orbital malignancy.

Diffusion-weighted imaging: Apparent diffusion coefficient histogram analysis for detecting pathologic complete response to chemoradiotherapy in locally advanced rectal cancer

PURPOSE

To investigate the usefulness of apparent diffusion coefficient (ADC) values derived from histogram analysis of the whole rectal cancer as a quantitative parameter to evaluate pathologic complete response (pCR) on preoperative magnetic resonance imaging (MRI).

MATERIALS AND METHODS

We enrolled a total of 86 consecutive patients who had undergone surgery for rectal cancer after neoadjuvant chemoradiotherapy (CRT) at our institution between July 2012 and November 2014. Two radiologists who were blinded to the final pathological results reviewed post-CRT MRI to evaluate tumor stage. Quantitative image analysis was performed using T2 -weighted and diffusion-weighted images independently by two radiologists using dedicated software that performed histogram analysis to assess the distribution of ADC in the whole tumor.

RESULTS

After surgery, 16 patients were confirmed to have achieved pCR (18.6%). All parameters from pre- and post-CRT ADC histogram showed good or excellent agreement between two readers. The minimum, 10th, 25th, 50th, and 75th percentile and mean ADC from post-CRT ADC histogram were significantly higher in the pCR group than in the non-pCR group for both readers. The 25th percentile value from ADC histogram in post-CRT MRI had the best diagnostic performance for detecting pCR, with an area under the receiver operating characteristic curve of 0.796.

CONCLUSION

Low percentile values derived from the ADC histogram analysis of rectal cancer on MRI after CRT showed a significant difference between pCR and non-pCR groups, demonstrating the utility of the ADC value as a quantitative and objective marker to evaluate complete pathologic response to preoperative CRT in rectal cancer. J. Magn. Reson. Imaging 2016;44:212-220.

Emerging Role of MRI for Radiation Treatment Planning in Lung Cancer

Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast and allows for specific scanning sequences to optimize differentiation between various tissue types and properties. Moreover, it offers the potential for real-time motion imaging. This makes magnetic resonance imaging an ideal candidate imaging modality for radiation treatment planning in lung cancer. Although the number of clinical research protocols for the application of magnetic resonance imaging for lung cancer treatment is increasing (www.clinicaltrials.gov) and the magnetic resonance imaging sequences are becoming faster, there are still some technical challenges. This review describes the opportunities and challenges of magnetic resonance imaging for radiation treatment planning in lung cancer.