Advances in diffusion-weighted imaging

The Apparent Diffusion Coefficient of the Paraspinal and Psoas Muscles Are of Prognostic Relevance in Patients With Hepatocellular Carcinoma Undergoing Transarterial Radioembolization

Background/Aim

Transarterial radioembolization (TARE) is a treatment option for early or intermediate stage hepatocellular carcinoma (HCC). Sarcopenia is defined as loss of muscle strength and quality which can be estimated by imaging modalities and has been associated with prognosis and treatment response in HCC patients. Apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) can reflect the tissue composition and might be better to determine muscle changes of sarcopenia than the standard method of computed tomography (CT). The present study sought to elucidate ADC values of the abdominal wall muscles as a prognostic factor in patients undergoing TARE.

Patients and Methods

A retrospective analysis was performed between 2016 and 2020. Overall, 52 patients, 9 women (17.3%) and 43 men (82.7%), with a mean age of 69±8.5 years were included into the analysis. In every case, the first pre-interventional magnetic resonance imaging (MRI) including DWI was used to measure the ADC values of paraspinal and psoas muscle. The 12-month survival after TARE was used as the primary study outcome.

Results

Overall, 40 patients (76.9%) of the patient cohort died within the 12-month observation period. Mean overall survival was 10.9 months after TARE for all patients. Mean ADC values for all muscles were 1.31±0.13×10-3mm2/s. The ADC values of the paraspinal muscles were statistically significantly higher compared to the ADC values of the psoas muscles (p=0.0031). A positive correlation was identified between mean ADC and the thrombocyte count (r=0.37, p=0.005) and serum bilirubin (r=-0.30, p=0.03). In the multivariate Cox regression analysis, the mean ADC values of all muscles were associated with the survival after 12 months (HR=0.98, 95% CI=0.97-0.99, p=0.04).

Conclusion

ADC values of the abdominal wall muscles could be used as a prognostic biomarker in patients with HCC undergoing TARE. These preliminary results should be confirmed by further studies using external validation cohorts and other treatment modalities.

O-RADS MRI risk stratification system: pearls and pitfalls

In 2021, the American College of Radiology (ACR) Ovarian-Adnexal Reporting and Data System (O-RADS) MRI Committee developed a risk stratification system and lexicon for assessing adnexal lesions using MRI. Like the BI-RADS classification, O-RADS MRI provides a standardized language for communication between radiologists and clinicians. It is essential for radiologists to be familiar with the O-RADS algorithmic approach to avoid misclassifications. Training, like that offered by International Ovarian Tumor Analysis (IOTA), is essential to ensure accurate and consistent application of the O-RADS MRI system. Tools such as the O-RADS MRI calculator aim to ensure an algorithmic approach. This review highlights the key teaching points, pearls, and pitfalls when using the O-RADS MRI risk stratification system.Critical relevance statement This article highlights the pearls and pitfalls of using the O-RADS MRI scoring system in clinical practice.Key points• Solid tissue is described as displaying post- contrast enhancement.• Endosalpingeal folds, fimbriated end of the tube, smooth wall, or septa are not solid tissue.• Low-risk TIC has no shoulder or plateau. An intermediate-risk TIC has a shoulder and plateau, though the shoulder is less steep compared to outer myometrium.

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.

The Feasibility of Using Tri-Exponential Intra-Voxel Incoherent Motion DWI for Identifying the Microvascular Invasion in Hepatocellular Carcinoma

Purpose

To assess the effectiveness of tri-exponential Intra-Voxel Incoherent Motion (tri-IVIM) MRI in preoperatively identifying microvascular invasion (MVI) in hepatocellular carcinoma (HCC).

Patients and Methods

In this prospective study, 67 patients with HCC were included. Metrics from bi-exponential IVIM (bi-IVIM) and tri-IVIM were calculated. Subgroup comparisons were analyzed using the independent Student's t-test or Mann-Whitney U-test. Logistic regression was performed to explore clinical risk factors. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis.

Results

MVI-positive HCCs exhibited significantly lower true diffusion coefficient (Dt) from bi-IVIM, as well as fast-diffusion coefficients (Df) and slow-diffusion coefficients (Ds) from tri-IVIM, compared to MVI-negative HCCs (p < 0.05). Tumor size and alpha-fetoprotein (AFP) were identified as risk factors. The combination of tri-IVIM-derived metrics (Ds and Df) yielded higher diagnostic accuracy (AUC = 0.808) compared to bi-IVIM (AUC = 0.741). A predictive model based on a nomogram was constructed using Ds, Df, tumor size, and AFP, resulting in the highest diagnostic accuracy (AUC = 0.859). Decision curve analysis indicated that the constructed model, provided the highest net benefit by accurately stratifying the risk of MVI, followed by tri-IVIM and bi-IVIM.

Conclusion

Tri-IVIM can provide information on perfusion and diffusion for evaluating MVI in HCC. Additionally, tri-IVIM outperformed bi-IVIM in identifying MVI-positive HCC. By integrating clinical risk factors and metrics from tri-IVIM, a predictive nomogram exhibited the highest diagnostic accuracy, potentially aiding in the noninvasive and preoperative assessment of MVI.

An MRI-based radiomics nomogram in predicting histologic grade of non-muscle-invasive bladder cancer

Background

Non-muscle-invasive bladder cancer (NMIBC) is categorized into high and low grades with different clinical treatments and prognoses. Thus, accurate preoperative evaluation of the histologic NMIBC grade through imaging techniques is essential.

Objectives

To develop and validate an MRI-based radiomics nomogram for individualized prediction of NMIBC grading.

Methods

The study included 169 consecutive patients with NMIBC (training cohort: n = 118, validation cohort: n = 51). A total of 3148 radiomic features were extracted, and one-way analysis of variance and least absolute shrinkage and selection operator were used to select features for building the radiomics score(Rad-score). Three models to predict NMIBC grading were developed using logistic regression analysis: a clinical model, a radiomics model and a radiomics–clinical combined nomogram model. The discrimination and calibration power and clinical applicability of the models were evaluated. The diagnostic performance of each model was compared by determining the area under the curve (AUC) in receiver operating characteristic (ROC) curve analysis.

Results

A total of 24 features were used to build the Rad-score. A clinical model, a radiomics model, and a radiomics–clinical nomogram model that incorporated the Rad-score, age, and number of tumors were constructed. The radiomics model and nomogram showed AUCs of 0.910 and 0.931 in the validation set, which outperformed the clinical model (0.745). The decision curve analysis also showed that the radiomics model and combined nomogram model yielded higher net benefits than the clinical model.

Conclusion

A radiomics–clinical combined nomogram model has the potential to be used as a non-invasive tool for the differentiating low-from high-grade NMIBCs.

Evaluation of pretreatment ADC values as predictors of treatment response to neoadjuvant chemotherapy in patients with breast cancer - a multicenter study

BACKGROUND

Magnetic resonance imaging (MRI) can be used to diagnose breast cancer. Diffusion weighted imaging (DWI) and the apparent diffusion coefficient (ADC) can reflect tumor microstructure in a non-invasive manner. The correct prediction of response of neoadjuvant chemotherapy (NAC) is crucial for clinical routine. Our aim was to compare ADC values between patients with pathological complete response (pCR) and non-responders based upon a multi-center design to improve the correct patient selection, which patient would more benefit from NAC and which patient would not.

METHODS

For this study, data from 4 centers (from Japan, Brazil, Spain and United Kingdom) were retrospectively acquired. The time period was overall 2003-2019. The patient sample comprises 250 patients (all female; median age, 50.5). In every case, pretreatment breast MRI with DWI was performed. pCR was assessed by experienced pathologists in every center using the surgical specimen in the clinical routine work up. pCR was defined as no residual invasive disease in either breast or axillary lymph nodes after NAC. ADC values between the group with pCR and those with no pCR were compared using the Mann-Whitney U test (two-group comparisons). Univariable and multivariabe logistic regression analysis was performed to predict pCR status.

RESULTS

Overall, 83 patients (33.2%) achieved pCR. The ADC values of the patient group with pCR were lower compared with patients without pCR (0.98 ± 0.23 × 10^- 3 mm²/s versus 1.07 ± 0.24 × 10^- 3 mm²/s, p = 0.02). The ADC value achieved an odds ratio of 4.65 (95% CI 1.40-15.49) in univariable analysis and of 3.0 (95% CI 0.85-10.63) in multivariable analysis (overall sample) to be associated with pCR status. The odds ratios differed in the subgroup analyses in accordance with the molecular subtype.

CONCLUSIONS

The pretreatment ADC-value is associated with pathological complete response after NAC in breast cancer patients. This could aid in clinical routine to reduce treatment toxicity for patients, who would not benefit from NAC. However, this must be tested in further studies, as the overlap of the ADC values in both groups is too high for clinical prediction.

The role of radiomics with machine learning in the prediction of muscle-invasive bladder cancer: A mini review

Bladder cancer is a common malignant tumor in the urinary system. Depending on whether bladder cancer invades muscle tissue, it is classified into non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). It is crucial to accurately diagnose the muscle invasion of bladder cancer for its clinical management. Although imaging modalities such as CT and multiparametric MRI play an important role in this regard, radiomics has shown great potential with the development and innovation of precision medicine. It features outstanding advantages such as non-invasive and high efficiency, and takes on important significance in tumor assessment and laor liberation. In this article, we provide an overview of radiomics in the prediction of muscle-invasive bladder cancer and reflect on its future trends and challenges.

The clinical value of dual-energy computed tomography and diffusion-weighted imaging in the context of liver cancer: A narrative review

The dual-energy computed tomography (DECT) and diffusion-weighted magnetic resonance imaging (DWI-MRI) are used to diagnose liver cancer. The clinical value of these two examination methods needs to be further summarized. We collected and summarized relevant literature published from 2011 to 2021. The diagnostic performance of DECT was assessed between conventional computed tomography and DWI-MRI. DWI-MRI had a 69% sensitivity for detecting small hepatocellular carcinoma (HCC) lesions and a 60% diagnostic specificity for differentiating between types of HCC lesions. DECT had a sensitivity to small liver lesions (<1 cm) of 69%, and the diagnostic specificity for HCC and metastasis was about 60%. DWI was more sensitive (90.3% vs. 74.9%) and accurate (91.9% vs. 76.9%) in diagnosing HCC compared with conventional MRI sequencing. With the aid of contrast media, DWI-MRI had 90.0% specificity for detecting small HCCs (smaller than 1 cm). Furthermore, DWI-MRI not only provided physicians with valuable diagnostic information but also delivered histological grading information, with 78% accuracy for all benign lesions and 71% for solid lesions. DECT had relatively high sensitivity and required a lower contrast medium dose. With standardized quantitative parameters, it can be an extremely useful tool for HCC surveillance. DWI-MRI is the preferred imaging process as it produces high-contrast images for supporting an early diagnosis (high sensitivity and specificity) and provides histological information using non-ionizing radiation.

The Value of Intravoxel Incoherent Motion Diffusion-Weighted Magnetic Resonance Imaging Combined With Texture Analysis of Evaluating the Extramural Vascular Invasion in Rectal Adenocarcinoma

Purpose

This study aims to evaluate the value of 3.0T MRI Intravoxel Incoherent motion diffusion-weighted magnetic resonance imaging (IVIM-DWI) combined with texture analysis (TA) for evaluating extramural vascular invasion (EMVI) of rectal adenocarcinoma.

Methods

Ninety-six patients with pathologically confirmed rectal adenocarcinoma after surgical resections were collected. Patients were divided into the EMVI positive group (n=39) and the EMVI negative group (n=57). We measured the IVIM-DWI parameters and TA parameters of rectal adenocarcinoma. We compare the differences of the above parameters between the two groups and establish a prediction model through multivariate logistic regression analysis. the ROC curve was performed for parameters with each individual and in combination.

Results

ADC, D, D* value between the two groups were statistically significant (P= 0.015,0.031,0). Six groups of texture parameters were statistically significant between the two groups (P=0.007,0.037,0.011,0.005,0.007,0.002). Logistic regression prediction model shows that GLCM entropy_ALL DIRECTION_offset7_SD and D* are important independent predictors, and the AUC of the regression prediction model was 0.821, the sensitivity was 92.98%, the specificity was 61.54%, and the Yoden index was 0.5452. The AUC was significantly higher than that of other single parameters.

Conclusion

3.0T MRI IVIM-DWI parameters combined with texture analysis can provide valuable information for EMVI evaluation of rectal adenocarcinoma before the operation.

Machine Learning in the Differentiation of Soft Tissue Neoplasms: Comparison of Fat-Suppressed T2WI and Apparent Diffusion Coefficient (ADC) Features-Based Models

Machine learning has been widely used in the characterization of tumors recently. This article aims to explore the feasibility of the whole tumor fat-suppressed (FS) T2WI and ADC features-based least absolute shrinkage and selection operator (LASSO)-logistic predictive models in the differentiation of soft tissue neoplasms (STN). The clinical and MR findings of 160 cases with 161 histologically proven STN were reviewed, retrospectively, 75 with diffusion-weighted imaging (DWI with b values of 50, 400, and 800 s/mm²). They were divided into benign and malignant groups and further divided into training (70%) and validation (30%) cohorts. The MR FS T2WI and ADC features-based LASSO-logistic models were built and compared. The AUC of the FS T2WI features-based LASSO-logistic regression model for benign and malignant prediction was 0.65 and 0.75 for the training and validation cohorts. The model's sensitivity, specificity, and accuracy of the validation cohort were 55%, 96%, and 76.6%. While the AUC of the ADC features-based model was 0.932 and 0.955 for the training and validation cohorts. The model's sensitivity, specificity, and accuracy were 83.3%, 100%, and 91.7%. The performances of these models were also validated by decision curve analysis (DCA). The AUC of the whole tumor ADC features-based LASSO-logistic regression predictive model was larger than that of FS T2WI features (p = 0.017). The whole tumor fat-suppressed T2WI and ADC features-based LASSO-logistic predictive models both can serve as useful tools in the differentiation of STN. ADC features-based LASSO-logistic regression predictive model did better than that of FS T2WI features.

Differentiating Glioblastomas from Solitary Brain Metastases: An Update on the Current Literature of Advanced Imaging Modalities

Differentiating between glioblastomas and solitary brain metastases proves to be a challenging diagnosis for neuroradiologists, as both present with imaging patterns consisting of peritumoral hyperintensities with similar intratumoral texture on traditional magnetic resonance imaging sequences. Early diagnosis is paramount, as each pathology has completely different methods of clinical assessment. In the past decade, recent developments in advanced imaging modalities enabled providers to acquire a more accurate diagnosis earlier in the patient's clinical assessment, thus optimizing clinical outcome. Dynamic susceptibility contrast has been optimized for detecting relative cerebral blood flow and relative cerebral blood volume. Diffusion tensor imaging can be used to detect changes in mean diffusivity. Neurite orientation dispersion and density imaging is an innovative modality detecting changes in intracellular volume fraction, isotropic volume fraction, and extracellular volume fraction. Magnetic resonance spectroscopy is able to assist by providing a metabolic descriptor while detecting variable ratios of choline/N-acetylaspartate, choline/creatine, and N-acetylaspartate/creatine. Finally, radiomics and machine learning algorithms have been devised to assist in improving diagnostic accuracy while often utilizing more than one advanced imaging protocol per patient. In this review, we provide an update on all the current evidence regarding the identification and differentiation of glioblastomas from solitary brain metastases.

Comparison and evaluation of distortion correction techniques on an MR-guided radiotherapy system

PURPOSE

To evaluate two distortion correction techniques for diffusion-weighted single-shot echo-planar imaging (DW-ssEPI) on a 0.35 T magnetic resonance-guided radiotherapy (MRgRT) system.

METHODS

The effects of sequence optimization through enabling parallel imaging (PI) and selecting appropriate bandwidth on spatial distortion were first evaluated on the 0.35 T MRgRT system using a spatial integrity phantom. Field map (FM) and reversed gradient (RG) corrections were then performed on the optimized protocol to further reduce distortion. An open-source toolbox was used to quantify the spatial displacement before and after distortion correction. To evaluate ADC accuracy and repeatability of the optimized protocol, as well as impacts of distortion correction on ADC values, the optimized protocol was scanned twice on a diffusion phantom. The calculated ADC values were compared with reference ADCs using paired t-test. Intraclass correlation coefficient (ICC) between the two repetitions, as well as between before and after FM/RG correction was calculated to evaluate ADC repeatability and effects of distortion correction. Six patients were recruited to assess the in-vivo performance. The optimal distortion correction technique was identified by visual assessment. To quantify distortion reduction, tumor and critical structures were contoured on the turbo spin echo (TSE) image (reference image), the DW-ssEPI image, and the distortion corrected images independently by two radiation oncologists. Mean distance to agreement (MDA) and DICE coefficient between contours on the reference images and the diffusion images were calculated. Tumor apparent diffusion coefficient (ADC) values from the original DW-ssEPI images and the distortion corrected images were compared using Bland-Altman analysis.

RESULTS

Sequence optimization played a vital role in improving the spatial integrity, and spatial distortion was proportional to the total readout time. Before the correction, distortion of the optimized protocol (PI and high bandwidth) was 1.50 ± 0.89 mm in a 100 mm radius and 2.21 ± 1.39 mm in a 175 mm radius for the central plane. FM corrections reduced the distortions to 0.42 ± 0.27 mm and 0.67 ± 0.49 mm respectively, and RG reduced distortion to 0.40 ± 0.22 mm and 0.64 ± 0.47 mm, respectively. The optimized protocol provided accurate and repeatable ADC quantification on the diffusion phantom. The calculated ADC values were consistent before and after FM/RG correction. For the patient study, the FM correction was unable to reduce chemical shift artifacts whereas the RG method successfully mitigated the chemical shift. MDA reduced from 2.52 ± 1.29 mm to 1.11 ± 0.72 mm after the RG correction. The DICE coefficient increased from 0.80 ± 0.13 to 0.91 ± 0.06. A Bland-Altman plot showed that there was a good agreement between ADC measurements before and after application of the RG correction.

CONCLUSION

Two distortion correction techniques were evaluated on a commercial low-field MRgRT system. Overall, the RG correction was able to drastically improve spatial distortion and preserve ADC accuracy.

Noninvasive Molecular Imaging of the Enhanced Permeability and Retention Effect by 64Cu-Liposomes: In vivo Correlations with 68Ga-RGD, Fluid Pressure, Diffusivity and 18F-FDG

Background

The accumulation of liposome encapsulated chemotherapy in solid cancers is dependent on the presence of the enhanced permeability and retention (EPR) effect. Positron emission tomography (PET) imaging with a liposome encapsulated radioisotope, such as liposome encapsulated Cu-64 (⁶⁴Cu-liposome) may help to identify tumors with high liposome accumulation, and thereby stratify patients based on expected benefit from liposomal chemotherapy. However, intravenous administration of liposomes without a cytotoxic content is complicated by the accelerated blood clearance (ABC) phenomenon for succeeding therapeutic liposome dosing. Alternative markers for assessing the tumor’s EPR level are therefore warranted.

Materials and Methods

To increase our understanding of EPR variations and to ultimately identify an alternative marker for the EPR effect, we investigated the correlation between ⁶⁴Cu-liposome PET/CT (EPR effect) and ⁶⁸Ga-RGD PET/CT (neoangiogenesis), ¹⁸F-FDG PET/CT (glycolysis), diffusion-weighted MRI (diffusivity) and interstitial fluid pressure in two experimental cancer models (CT26 and COLO 205).

Results

⁶⁴Cu-liposome and ⁶⁸Ga-RGD SUV_max displayed a significant moderate correlation, however, none of the other parameters evaluated displayed significant correlations. These results indicate that differences in neoangiogenesis may explain some EPR variability, however, as correlations were only moderate and not observed for SUV_mean, ⁶⁸Ga-RGD is probably insufficient to serve as a stand-alone surrogate marker for quantifying the EPR effect and stratifying patients.

Comparative Study of Monoexponential, Intravoxel Incoherent Motion, Kurtosis, and IVIM-Kurtosis Models for the Diagnosis and Aggressiveness Assessment of Prostate Cancer

Objective: This study aimed to compare the potential of monoexponential model (MEM), intravoxel incoherent motion (IVIM) model, kurtosis model, and IVIM–kurtosis model in the diagnosis and aggressiveness assessment of prostate cancer (PCa).

Materials and Methods: Thirty-six patients were recruited. Diffusion-weighted images were acquired on a 3.0-T magnetic resonance imaging (MRI) system using 0 b values up to 2,000 s/mm² and analyzed using four models: MEM (ADC_MEM), IVIM (D_IVIM, D*_IVIM, f_IVIM), kurtosis (D_kurtosis, K_kurtosis), and IVIM–kurtosis (D_{IVIM−kurtosis}, D^*_{IVIM−kurtosis}, f_{IVIM−kurtosis}, D_{IVIM−kurtosis}) models. The values of these parameters were calculated and compared between PCa, benign prostatic hyperplasia (BPH), and prostatitis. Correlations between these parameters and the Gleason score (GS) of PCa were evaluated using the Pearson test.

Results: Forty-five lesions were studied, including 18 PCa, 12 prostatitis, and 15 BPH lesions. The ADC_MEM, D_IVIM, f_IVIM, D_kurtosis, and D_{IVIM−kurtosis} values were significantly lower and K_kurtosis and K_{IVIM−kurtosis} values were significantly higher in PCa compared with prostatitis and BPH. The area under the curve (AUC) of ADC_MEM showed significantly higher values than that of f_IVIM and K_{IVIM−kurtosis}, but no statistical differences were found between the other parameters. The D^*_{IVIM−kurtosis} value correlated negatively and f_{IVIM−kurtosis} and K_{IVIM−kurtosis} values correlated positively with the GS.

Conclusion: The MEM, IVIM, kurtosis, and IVIM–kurtosis models were all useful for the diagnosis of PCa, and the diagnostic efficacy seemed to be similar. The IVIM–kurtosis model may be superior to the MEM, IVIM, and kurtosis models in the grading of PCa.

Multiple b-value diffusion-weighted imaging in differentiating benign from malignant breast lesions: comparison of conventional mono-, bi- and stretched exponential models

AIM

To prospectively evaluate multiple b-value diffusion-weighted imaging (DWI) in differentiating malignant from benign breast lesions.

MATERIALS AND METHODS

The study cohort included 103 patients who underwent 3 T magnetic resonance imaging (MRI). The conventional sequences included T1-weighted dynamic contrast-enhanced, T1-weighted and T2-weighted fat-suppressed sequences, single b-value (b=0, 1000 s/mm²) DWI, and multiple b-values (12 values, from 0 to 3,000 s/mm²) DWI. Pathological diagnosis of breast lesions was based on the latest World Health Organization (WHO) guide on the pathology and immunohistochemistry of the breast. SPSS Statistics V19.0 was used for the statistics analysis.

RESULTS

The following parameters were calculated: apparent diffusion coefficient (ADC), tissue diffusivity (D), perfusion fraction (f), pseudo-diffusion coefficient (D∗), distributed diffusion coefficient (DDC), and alpha (α) by the same radiologist twice (interval time of 3 months). There was good inter/intra-observer agreement for each of the parameters. The D, D∗, f, DDC, and α values were significantly different among malignant tumours, benign lesions, and normal breast tissue (p<0.05).

CONCLUSION

D, f, DDC, α, and ADC values have good sensitivity and specificity, respectively. In addition, the combined use of D and f or DDC and α has good diagnostic performance. Thus, the applications of the new multi-b DWI variables or combined variables are promising.

Exploring in vivo placental microstructure in healthy and growth-restricted pregnancies through diffusion-weighted magnetic resonance imaging

INTRODUCTION

Gross and microstructural changes in placental development can influence placental function and adversely impact fetal growth and well-being; however, there is a paucity of invivo tools available to reliably interrogate in vivo placental microstructural development. The objective of this study is to characterize invivo placental microstructural diffusion and perfusion in healthy and growth-restricted pregnancies (FGR) using non-invasive diffusion-weighted imaging (DWI).

METHODS

We prospectively enrolled healthy pregnant women and women whose pregnancies were complicated by FGR. Each woman underwent DWI-MRI between 18 and 40 weeks gestation. Placental measures of small (D) and large (D*) scale diffusion and perfusion (f) were estimated using the intra-voxel incoherent motion (IVIM) model.

RESULTS

We studied 137 pregnant women (101 healthy; 36 FGR). D and D* are increased in late-onset FGR, and the placental perfusion fraction, f, is decreased (p < 0.05 for all).

DISCUSSION

Placental DWI revealed microstructural alterations of the invivo placenta in FGR, particularly in late-onset FGR. Early and reliable identification of placental pathology in vivo may better guide future interventions.

Quantitative Multiparametric MRI May Augment the Response to Radiotherapy in Mid-Treatment Assessment of Patients with Esophageal Carcinoma

OBJECTIVE

The purpose of this study was to assess the mid-treatment response to radiotherapy (RT) using dynamic contrast-enhanced MRI (DCE-MRI) and diffusion-weighted imaging (DWI) in patients with esophageal cancer (EC).

METHODS

42 patients with squamous EC were prepared for DCE-MRI and DWI scans both before treatment (NRT) and after the fifth radiotherapy (5th RT). The patients were classified into two groups (complete response [CR] and partial response [PR]) according to tumor regression after treatment. The quantitative parameters of DCE-MRI (Ktrans, Kep, Ve, and ADC) were measured. A receiver operating characteristic curve (ROC) was used to detect the efficiency of the above parameters.

RESULTS

After 1 month of RT, 29 patients were classified as CR and 11 patients were classified as PR. In the NRT group, the p values of Ktrans, Kep, Ve, and ADC were 0.004, 0.078, 0.0008, and <0.0001, respectively. After the 5th RT, the p values of the above parameters were <0.001, 0.005, 0.108, and 0.365, respectively. In the NRT group, the areas under the ROC curves of Ktrans, Ve, and ADC were 0.790, 0.617, and 0.737; the sensitivity values were 89.3, 92.5, and 90.0%; the specificity values were 69.4, 27.5, and 50.0%. In the 5th RT group, the areas under the ROC curves of Ktrans and Kep were 0.816 and 0.804; the sensitivity values were 71.2 and 95.0%; the specificity values were 81.6 and 50.0%.

CONCLUSION

DCE-MRI combined with DWI is effective in the early prediction of radiotherapeutic response of EC after the 5th RT other than after the traditional final treatment.

Use of Quantitative T2-Weighted and Apparent Diffusion Coefficient Texture Features of Bladder Cancer and Extravesical Fat for Local Tumor Staging After Transurethral Resection

OBJECTIVE. The purpose of this study was to determine whether quantitative T2-weighted imaging and apparent diffusion coefficient (ADC) texture features of bladder cancer and extravesical fat are predictive of muscle invasive bladder cancer (category ≥ T2) and extravesical (category ≥ T3) disease after transurethral resection of a bladder tumor (TURBT). MATERIALS AND METHODS. In this retrospective study, 36 patients (27 men, nine women; mean age, 71 years) were identified who underwent post-TURBT MRI followed by cystectomy without intervening treatment from August 2011 through October 2016. Texture features of bladder cancer and extravesical fat adjacent to the tumor on T2-weighted and ADC images were extracted and compared between category ≤ T2 versus ≥ T3 and category T1 versus ≥ T2 tumors by means of Kruskal-Wallis or Mann-Whitney U test. Multivariate logistic regression analysis was performed, and ROC curves were calculated. RESULTS. Twenty-six of the 36 (72%) tumors were ≥ T2, and 53% (19/36) were ≥ T3. In multivariate analysis, bladder cancer entropy on T2-weighted images (p = 0.006; odds ratio [OR], 4.56; 95% CI, 1.49-20.41; AUC, 0.85) and ADC maps (p = 0.019; OR, 2.24; 95% CI, 1.13-5.31; AUC, 0.80) and extravesical fat entropy on T2-weighted images (p = 0.005; OR, 17.50; 95% CI, 3.01-200.80; AUC, 0.84) and ADC maps (p = 0.002; OR, 6.54; 95% CI, 1.90-32.40; AUC, 0.82) remained greater for ≥ T3 than for ≤ T2 tumors. In multivariate analysis, bladder cancer entropy on ADC maps (p = 0.027; OR, 2.11; 95% CI, 1.08-5.03; AUC, 0.76) and extravesical fat entropy on T2-weighted images (p = 0.010; OR, 5.33; 95% CI, 1.25-3.79; AUC, 0.78) and ADC maps (p = 0.029; OR, 3.80; 95% CI, 1.25-16.97; AUC, 0.74) remained greater for category ≥ T2 compared with category T1 tumors. CONCLUSION. Greater entropy of primary bladder cancers and extravesicular fat was observed in category ≥ T3 than in category ≤ T2 and in category ≥ T2 than in category T1 tumors. MRI texture analysis can help with local bladder cancer staging in patients who have undergone TURBT and may serve as a biomarker for higher local category bladder cancers.

Hepatocellular carcinoma: Can LI-RADS v2017 with gadoxetic-acid enhancement magnetic resonance and diffusion-weighted imaging improve diagnostic accuracy?

BACKGROUND

The Liver Imaging Reporting and Data System (LI-RADS), supported by the American College of Radiology (ACR), has been developed for standardizing the acquisition, interpretation, reporting, and data collection of liver imaging examinations in patients at risk for hepatocellular carcinoma (HCC). Diffusion-weighted imaging (DWI), which is described as an ancillary imaging feature of LI-RADS, can improve the diagnostic efficiency of LI-RADS v2017 with gadoxetic acid-enhanced magnetic resonance imaging (MRI) for HCC.

AIM

To determine whether the use of DWI can improve the diagnostic efficiency of LI-RADS v2017 with gadoxetic acid-enhanced magnetic resonance MRI for HCC.

METHODS

In this institutional review board-approved study, 245 observations of high risk of HCC were retrospectively acquired from 203 patients who underwent gadoxetic acid-enhanced MRI from October 2013 to April 2018. Two readers independently measured the maximum diameter and recorded the presence of each lesion and assigned scores according to LI-RADS v2017. The test was used to determine the agreement between the two readers with or without DWI. In addition, the sensitivity (SE), specificity (SP), accuracy (AC), positive predictive value (PPV), and negative predictive value (NPV) of LI-RADS were calculated. Youden index values were used to compare the diagnostic performance of LI-RADS with or without DWI.

RESULTS

Almost perfect interobserver agreement was obtained for the categorization of observations with LI-RADS (kappa value: 0.813 without DWI and 0.882 with DWI). For LR-5, the diagnostic SE, SP, and AC values were 61.2%, 92.5%, and 71.4%, respectively, with or without DWI; for LR-4/5, they were 73.9%, 80%, and 75.9% without DWI and 87.9%, 80%, and 85.3% with DWI; for LR-4/5/M, they were 75.8%, 58.8%, and 70.2% without DWI and 87.9%, 58.8%, and 78.4% with DWI; for LR- 4/5/TIV, they were 75.8%, 75%, and 75.5% without DWI and 89.7%, 75%, and 84.9% with DWI. The Youden index values of the LI-RADS classification without or with DWI were as follows: LR-4/5: 0.539 vs 0.679; LR-4/5/M: 0.346 vs 0.467; and LR-4/5/TIV: 0.508 vs 0.647.

CONCLUSION

LI-RADS v2017 has been successfully applied with gadoxetate-enhanced MRI for patients at high risk for HCC. The addition of DWI significantly increases the diagnostic efficiency for HCC.

Comparison of Navigator Triggering Reduced Field of View and Large Field of View Diffusion-Weighted Imaging of the Pancreas

RATIONALE AND OBJECTIVES

The purpose of this study is to compare image quality, presence and grade of artifacts, signal-to-noise ratio, and apparent diffusion coefficient (ADC) values in pancreatic tissue between high-resolution navigator-triggered (NT) restricted field of view (rFOV) FOCUS single-shot (SS) echo-planar imaging (EPI) diffusion-weighted imaging (DWI) and NT large FOV SS-EPI DWI.

MATERIALS AND METHODS

Magnetic resonance imaging examinations were performed with GE 3-T systems using a 32-channel body array coil. Seventeen consecutive patients were imaged. A 5-point scale semiquantitative grading system was used to evaluate image quality and general artifacts. Signal-to-noise ratio and ADC were measured in the head, body, and tail of the pancreas. Statistical analysis was performed using Student t test and Wilcoxon signed rank test, with differences considered significant for P value less than 0.05.

RESULTS

More artifacts were present on large FOV compared with rFOV FOCUS SS-EPI DW images (P < 0.01). Restricted field of view image quality was subjectively better (P < 0.01). No difference in the signal-to-noise ratio was demonstrated between the 2 image datasets. Apparent diffusion coefficient values were significantly lower (P < 0.01) when calculated from rFOV images than large FOV images.

CONCLUSIONS

Our results demonstrate better image quality and reduced artifacts in rFOV images compared with large FOV DWI. Measurements from ADC maps derived from rFOV DWI show significantly lower ADC values when compared with ADC maps derived from large FOV DWI.

State of the art in magnetic resonance imaging of hepatocellular carcinoma

Background

Liver cancer is the sixth most common cancer worldwide and the second leading cause of cancer mortality. Chronic liver disease caused by viral infection, alcohol abuse, or other factors can lead to cirrhosis. Cirrhosis is the most important clinical risk factor for hepatocellular carcinoma (HCC) whereby the normal hepatic architecture is replaced by fibrous septa and a spectrum of nodules ranging from benign regenerative nodules to HCC, each one of them with different imaging features.

Conclusions

Furthermore, advanced techniques including the quantification of hepatic and intralesional fat and iron, magnetic resonance elastography, radiomics, radiogenomics, and positron emission tomography (PET)-MRI are highly promising for the extraction of new imaging biomarkers that reflect the tumor microenvironment and, in the future, may add decision-making value in the management of patients with HCC.

Quantitative Identification of Nonmuscle-Invasive and Muscle-Invasive Bladder Carcinomas: A Multiparametric MRI Radiomics Analysis

BACKGROUND

Preoperative discrimination between nonmuscle-invasive bladder carcinomas (NMIBC) and the muscle-invasive ones (MIBC) is very crucial in the management of patients with bladder cancer (BC).

PURPOSE

To evaluate the discriminative performance of multiparametric MRI radiomics features for precise differentiation of NMIBC from MIBC, preoperatively.

STUDY TYPE

Retrospective, radiomics.

POPULATION

Fifty-four patients with postoperative pathologically proven BC lesions (24 in NMIBC and 30 in MIBC groups) were included.

FIELD STRENGTH/SEQUENCE

3.0T MRI/T₂ -weighted (T₂ W) and multi-b-value diffusion-weighted (DW) sequences.

ASSESSMENT

A total of 1104 radiomics features were extracted from carcinomatous regions of interest on T₂ W and DW images, and the apparent diffusion coefficient maps. Support vector machine with recursive feature elimination (SVM-RFE) and synthetic minority oversampling technique (SMOTE) were used to construct an optimal discriminative model, and its performance was evaluated and compared with that of using visual diagnoses by experts.

STATISTICAL TESTS

Chi-square test and Student's t-test were applied on clinical characteristics to analyze the significant differences between patient groups.

RESULTS

Of the 1104 features, an optimal subset involving 19 features was selected from T₂ W and DW sequences, which outperformed the other two subsets selected from T₂ W or DW sequence in muscle invasion discrimination. The best performance for the differentiation task was achieved by the SVM-RFE+SMOTE classifier, with averaged sensitivity, specificity, accuracy, and area under the curve of receiver operating characteristic of 92.60%, 100%, 96.30%, and 0.9857, respectively, which outperformed the diagnostic accuracy by experts.

DATA CONCLUSION

The proposed radiomics approach has potential for the accurate differentiation of muscle invasion in BC, preoperatively. The optimal feature subset selected from multiparametric MR images demonstrated better performance in identifying muscle invasiveness when compared with that from T₂ W sequence or DW sequence only.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1489-1498.

Effect of flow-encoding strength on intravoxel incoherent motion in the liver

PURPOSE

To study the impact of variable flow-encoding strength on intravoxel incoherent motion (IVIM) liver imaging of diffusion and perfusion.

THEORY

Signal attenuation in DWI arises from (1) intravoxel microvascular blood flow, which depends on the flow-encoding strength α (first gradient moment) of the diffusion-encoding waveform, and (2) intravoxel spin diffusion, which depends on the b-value of the diffusion-encoding gradient waveforms α and b-value. Both are linked to the diffusion-encoding gradient waveform and conventionally are not independently controlled.

METHODS

In this work a convex optimization framework was used to generate gradient waveforms with independent α and b-value. Thirty-six unique α and b-value sample points from 5 different gradient waveforms were used to reconstruct perfusion fraction (f), coefficient of diffusion (D), and blood velocity standard deviation (V_b ) maps using a recently proposed IVIM model. Faster acquisition strategies were evaluated with 1000 random subsampling strategies of 16, 8, and 4 α and b-value. Among the subsampled reconstructions, the sampling schemes that minimized the difference with the fully sampled reconstruction were reported.

RESULTS

Healthy volunteers (N = 9) were imaged on a 3T scanner. Liver perfusion and diffusion estimates using the fully sampled IVIM method were f = 0.19 ± 0.06, D = 1.15 ± 0.15 × 10^-3 mm² /s, and V_b = 5.22 ± 3.86 mm/s. No statistical differences were found between the fully sampled and 2-times undersampled reconstruction (f = 0.2 ± 0.07, D = 1.19 ± 0.15 × 10^-3 mm² /s, V_b = 5.79 ± 3.43 mm/s); 4-times undersampled (f = 0.2 ± 0.06, D = 1.15 ± 0.17 × 10^-3 mm² /s, V_b = 4.66 ± 3.61 mm/s), or 8-times undersampled ( f = 0.2 ± 0.06, D = 1.23 ± 0.22 × 10^-3 mm² /s, V_b = 4.99 ± 3.82 mm/s) approaches.

CONCLUSION

We demonstrate the IVIM signal's dependence on the b-value, the diffusion-encoding time and the flow-encoding strength and observe in vivo the ballistic regime signature of microperfusion in the liver. This work also demonstrates that using an IVIM model and sampling scheme matched to the ballistic regime, pixel-wise IVIM parameter maps are possible when sampling as few as 4 IVIM signals.

Does Second Reader Opinion Affect Patient Management in Pancreatic Ductal Adenocarcinoma?

RATIONALE AND OBJECTIVES

To determine the impact of second-opinion assessment on cancer staging and patient management in patients with pancreatic ductal adenocarcinoma.

METHODS AND MATERIALS

This retrospective study was approved by our institutional review board with a waiver of informed consent. Second-opinion reports between January 1, 2009 and December 31, 2013, alongside outside reports for 65 consecutive cases of biopsy-proven pancreatic adenocarcinomas, were presented in random order to two experienced abdominal surgeons who independently reviewed them blinded to the origin of the report, images of the examinations, and patient identifier. Each surgeon filled in a questionnaire for each report recommending cancer staging and patient management. Recommended patient management and staging were evaluated against reference standards (actual patient management at 6 months following second-opinion assessment, and pathology or other clinical and imaging reference standards at 6 months or longer, respectively) using Cohen kappa.

RESULTS

Cancer staging differed in 13% (9 of 65) of cases for surgeon 1 and in 18.4% (12 of 65) for surgeon 2. Patient management changed in 38.4% (25 of 65) of cases for surgeon 1 and in 20% (13 of 65) for surgeon 2. When compared to the pathologic staging gold standard, second opinion was correct in 85.7% (six of seven) of the time for both surgeons. Recommended patient management from second-opinion reports showed good agreement with the reference standard (weighted k = 0.6467 [0.4014-0.892] and weighted k = 0.6262 [0.3954-0.857] for surgeon 2).

CONCLUSION

Second-opinion review by subspecialized oncologic radiologists can impact patient care, specifically in terms of management decision.

Diffusion-weighted imaging in evaluating the efficacy of concurrent chemoradiotherapy in the treatment of non-small cell lung cancer

Objective:

To explore the predictive value of diffusion-weighted imaging (DWI) in evaluating the short-term efficacy of concurrent chemoradiotherapy (CCRT) in the treatment of patients with non-small cell lung cancer (NSCLC).

Methods:

A total of 192 patients with NSCLC were selected and treated with CCRT. Dynamic contrast-enhanced magnetic resonance imaging combined with DWI was performed on all patients before and after CCRT treatment. Correspondingly, apparent diffusion coefficient (ADC) values were recorded before treatment (ADCpre), during treatment (ADCmid), and after treatment (ADCpost). Tumor response was evaluated as complete response (CR), partial response (PR), stable disease (SD), or progressive disease (PD). Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic power of quantitative DWI parameters in predicting the short-term efficacy of CCRT for patients with NSCLC.

Results:

There were 21 patients with CR, 82 with PR, 77 with SD, and 12 with PD. The ADCpre was negatively correlated with tumor regression rate, whereas ADCmid, ADCpost, and their respective change rates ∆ADCmid and ∆ADCpost were positively related to tumor regression rate. The ROC curve analysis suggested ADCpre = 1.38 × 10−3 mm2/s, ∆ADCmid = 14.14%, and ∆ADCpost = 20.39% as thresholds to predict the short-term efficacy of CCRT, with corresponding areas under the curve of 0.637, 0.743, and 0.752, respectively.

Conclusions:

These findings indicate that DWI provides promising predictive value in evaluating the short-term efficacy of CCRT in the treatment of patients with NSCLC.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging of Primary Rectal Carcinoma: Correlation with Histopathology

BACKGROUND Comprehensive and precise assessment of rectal carcinoma is crucial before surgery to plan an individual treatment strategy. New functional techniques, such as intravoxel incoherent motion (IVIM), have emerged and could lead to more detailed information. The aim of this study was to evaluate the difference between the rectal tumor parenchyma and normal wall by IVIM and to explore the correlations of IVIM parameters and histopathology. MATERIAL AND METHODS We prospectively enrolled 128 patients with pathologically proven rectal non-mucinous carcinoma with differentiation degree and 16 patients with mucinous carcinoma. All patients underwent routine MR examination and IVIM sequence. The IVIM maps were automatically generated and 3 ROIs were drawn on the maximal rectal tumor parenchyma and normal rectal wall. The Wilcoxon signed rank test, t test, Mann-Whitney U test, and Spearman's rank correlation test were performed. RESULTS All IVIM parameters demonstrated the difference between rectal tumor parenchyma and normal wall (PD<0.001; PD*=0.014; Pf<0.001). Poorly differentiated carcinoma had a significantly lower f value (Pf=0.049) than well/moderately-differentiated carcinoma. In addition, mucinous carcinoma had a higher D (PD=0.001) and a lower D* value (PD*=0.001) than non-mucinous carcinoma. Correlation analysis between IVIM parameters and histopathology showed that D (|r|=0.538, PD=0.000) and D* (|r|=0.267, PD*=0.001) had statistically significant correlations with histological type and f (|r|=0.175, Pf=0.048) was significantly correlated with differentiation degree. CONCLUSIONS The IVIM parameters of rectal tumor parenchyma and normal wall were significantly different. D appears to be a valid and promising parameter to indicate histological features of rectal carcinoma.

Intravoxel Incoherent Motion Diffusion-Weighted Imaging of Primary Rectal Carcinoma: Correlation with Histopathology

Background

Comprehensive and precise assessment of rectal carcinoma is crucial before surgery to plan an individual treatment strategy. New functional techniques, such as intravoxel incoherent motion (IVIM), have emerged and could lead to more detailed information. The aim of this study was to evaluate the difference between the rectal tumor parenchyma and normal wall by IVIM and to explore the correlations of IVIM parameters and histopathology.

Material/Methods

We prospectively enrolled 128 patients with pathologically proven rectal non-mucinous carcinoma with differentiation degree and 16 patients with mucinous carcinoma. All patients underwent routine MR examination and IVIM sequence. The IVIM maps were automatically generated and 3 ROIs were drawn on the maximal rectal tumor parenchyma and normal rectal wall. The Wilcoxon signed rank test, t test, Mann-Whitney U test, and Spearman’s rank correlation test were performed.

Results

All IVIM parameters demonstrated the difference between rectal tumor parenchyma and normal wall (P_D<0.001; P_D*=0.014; P_f<0.001). Poorly differentiated carcinoma had a significantly lower f value (P_f=0.049) than well/moderately-differentiated carcinoma. In addition, mucinous carcinoma had a higher D (P_D=0.001) and a lower D* value (P_D*=0.001) than non-mucinous carcinoma. Correlation analysis between IVIM parameters and histopathology showed that D (|r|=0.538, P_D=0.000) and D* (|r|=0.267, P_D*=0.001) had statistically significant correlations with histological type and f (|r|=0.175, P_f=0.048) was significantly correlated with differentiation degree.

Conclusions

The IVIM parameters of rectal tumor parenchyma and normal wall were significantly different. D appears to be a valid and promising parameter to indicate histological features of rectal carcinoma.

Hepatic angiosarcomatous transformation of a mediastinal germinal cell tumor: A care case report

RATIONALE

Mediastinal nonseminomatous germ cell tumor (NSGCT) is an uncommon entity. Metastatic hepatic sarcomatous transformation is rare.

PATIENT CONCERNS

We report a 24-year-old man with no previous related medical history presented with chest pain and left arm numbness.

DIAGNOSES

The x-ray showed an anterior mediastinal mass. The chest computed tomography (CT) confirmed the presence of a mildly enhancing mass in the same location, without invasion of any vascular structure. A CT-guided biopsy was performed, revealing a primary mediastinal nonseminomatous germ cell tumor (NSGCT), yolk sac histology, with areas of somatic transformation to malignant nerve sheath tumor. After surgery patient was followed-up with imaging. Two years later a CT scan showed a new hepatic hyper vascular lesion, confirmed by a subsequent magnetic resonance imaging (MRI) and positron emission tomography (PET) scan. A CT-guided biopsy revealed a hepatic metastatic transformation to angiosarcoma of the primitive NSGCT.

INTERVENTIONS

The patient went on to received palliative chemotherapy.

OUTCOMES

The patient is being followed-up regularly at the outpatient department.

LESSONS

Because of the potential of metastatic sarcoma arising from germ cell tumors, these patients should undergo periodical follow-up, with periodical scans. PET\CT scan might have a role in the follow-up of these patients.

Subclinical focal Cholangitis mimicking liver metastasis in asymptomatic patients with history of pancreatic Ductal Adenocarcinoma and Biliary tree intervention

Background

Cholangitis is an inflammatory process of the biliary tract with a wide range of clinical manifestations and it is not always considered in the differential diagnosis in asymptomatic patients. To the best of our knowledge there is no previous report in the English literature of focal cholangitis manifesting exclusively as liver parenchymal changes mimicking liver metastasis in asymptomatic patients with pancreatic ductal adenocarcinoma (PDAC) and history of manipulation of the biliary tree. The purpose of this article is to present six cases of subclinical focal cholangitis mimicking liver metastasis in asymptomatic patients with history of PDAC and biliary tree intervention.

Case presentation

There are six cases with new hepatic lesions detected on follow-up scans in asymptomatic patients with history of PDAC and manipulation of biliary tree. Overall seven lesions were detected, all of them were on the liver periphery, five were hypovascular and two were hypervascular. None of those patients had elevation of CA 19.9 compared with the previous exams. The three patients that had magnetic resonance imaging presented restriction on diffusion weighted imaging and high signal intensity on T2-weighted image. Two patients underwent liver biopsy, which showed only inflammatory changes. All patients were treated with antibiotics and underwent imaging follow-up, which demonstrated resolution of the lesions. None of the patients showed imaging or clinical signs of disease progression during this interval.

Conclusion

Radiologists and oncologists need to be aware of the possibility of focal cholangitis causing hepatic lesions mimicking neoplasia in patients with history of biliary tree intervention, even in the absence of clinical symptoms.

Radiomics assessment of bladder cancer grade using texture features from diffusion-weighted imaging

PURPOSE

To 1) describe textural features from diffusion-weighted images (DWI) and apparent diffusion coefficient (ADC) maps that can distinguish low-grade bladder cancer from high-grade, and 2) propose a radiomics-based strategy for cancer grading using texture features.

MATERIALS AND METHODS

In all, 61 patients with bladder cancer (29 in high- and 32 in low-grade groups) were enrolled in this retrospective study. Histogram- and gray-level co-occurrence matrix (GLCM)-based radiomics features were extracted from cancerous volumes of interest (VOIs) on DWI and corresponding ADC maps of each patient acquired from 3.0T magnetic resonance imaging (MRI). A Mann-Whitney U-test was applied to select features with significant differences between low- and high-grade groups (P < 0.05). Then support vector machine with recursive feature elimination (SVM-RFE) and classification strategy was adopted to find an optimal feature subset and then to establish a classification model for grading.

RESULTS

A total 102 features were derived from each VOI and among them, 47 candidate features were selected, which showed significant intergroup differences (P < 0.05). By the SVM-RFE method, an optimal feature subset including 22 features was further selected from candidate features. The SVM classifier using the optimal feature subset achieved the best performance in bladder cancer grading, with an area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity of 0.861, 82.9%, 78.4%, and 87.1%, respectively.

CONCLUSION

Textural features from DWI and ADC maps can reflect the difference between low- and high-grade bladder cancer, especially those GLCM features from ADC maps. The proposed radiomics strategy using these features, combined with the SVM classifier, may better facilitate image-based bladder cancer grading preoperatively.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1281-1288.

Longitudinal diffusion MRI for treatment response assessment: Preliminary experience using an MRI-guided tri-cobalt 60 radiotherapy system

PURPOSE

To demonstrate the preliminary feasibility of a longitudinal diffusion magnetic resonance imaging (MRI) strategy for assessing patient response to radiotherapy at 0.35 T using an MRI-guided radiotherapy system (ViewRay).

METHODS

Six patients (three head and neck cancer, three sarcoma) who underwent fractionated radiotherapy were enrolled in this study. A 2D multislice spin echo single-shot echo planar imaging diffusion pulse sequence was implemented on the ViewRay system and tested in phantom studies. The same pulse sequence was used to acquire longitudinal diffusion data (every 2-5 fractions) on the six patients throughout the entire course of radiotherapy. The reproducibility of the apparent diffusion coefficient (ADC) measurements was assessed using reference regions and the temporal variations of the tumor ADC values were evaluated.

RESULTS

In diffusion phantom studies, the ADC values measured on the ViewRay system matched well with reference ADC values with <5% error for a range of ground truth diffusion coefficients of 0.4-1.1 × 10(-3) mm(2)/s. The remote reference regions (i.e., brainstem in head and neck patients) had consistent ADC values throughout the therapy for all three head and neck patients, indicating acceptable reproducibility of the diffusion imaging sequence. The tumor ADC values changed throughout therapy, with the change differing between patients, ranging from a 40% drop in ADC within the first week of therapy to gradually increasing throughout therapy. For larger tumors, intratumoral heterogeneity was observed. For one sarcoma patient, postradiotherapy biopsy showed less than 10% necrosis score, which correlated with the observed 40% decrease in ADC from the fifth fraction to the eighth treatment fraction.

CONCLUSIONS

This pilot study demonstrated that longitudinal diffusion MRI is feasible using the 0.35 T ViewRay MRI. Larger patient cohort studies are warranted to correlate the longitudinal diffusion measurements to patient outcomes. Such an approach may enable response-guided adaptive radiotherapy.

Could ADC values be a promising diagnostic criterion for differentiating malignant and benign hepatic lesions in Asian populations: A meta-analysis

BACKGROUND

Liver cancer exhibits geographic and ethnic differences in its prevalence and biology, which implies that it is impractical to develop universal guidelines for all patients. Thus, a meta-analysis was conducted to identify the accuracy of apparent diffusion coefficients (ADCs) for discriminating malignant from benign liver lesions in Asians.

METHODS

Eligible studies published in PubMed, Ovid, and Embase/Medline were updated onto October 2014. STATA 12.0 and Meta-Disc 1.4 were used to perform this meta-analysis.

RESULTS

Eight studies comprising 661 benign liver lesions and 598 malignant liver lesions fulfilled all the inclusion criteria. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.88 (95% confidence interval [CI] 0.75-0.95), 0.93 (95% CI 0.86-0.97), 12.42 (95% CI 6.09-25.31), 0.13 (95% CI 0.06-0.29), and 95.58 (95% CI 35.29-258.89), respectively. Overall, the area under the summary receiver-operating characteristic curve was 0.96 (95% CI 0.94-0.98). Heterogeneity was found to originate potentially from the type of benign lesion. A subgroup analysis showed that differentiating between hemangiomas, cysts, and malignant liver lesions produced a significantly higher diagnostic accuracy than that of solid liver lesions.

CONCLUSION

Our meta-analysis indicated that ADC could be promising for characterizing liver lesions among Asians, indicating that the ADC value is a promising diagnostic criterion candidate. Meanwhile, the use of dual b values could be sufficient for liver lesion characterization. However, large-scale, high-quality trials should be conducted to identify specific standards, including cut-off values for further development of diffusion-weighted imaging as a routine clinical application among Asian populations.

Black blood T1rho MR imaging may diagnose early stage liver fibrosis: a proof-of-principle study with rat biliary duct ligation model

BACKGROUND

To explore black blood T1rho (T1ρ) liver imaging and investigate the earliest stage when biliary duct ligation (BDL) induced liver fibrosis can be diagnosed.

METHODS

MR was performed at 3 Tesla. A T1ρ prepared 2D fast spin echo (FSE) sequence with acquisition of four spin lock times (TSLs: 1, 10, 30, and 50 msec) and spin-lock frequency of 500 Hz was applied. Inherent black blood effect of FSE and double inversion recovery (DIR) achieved blood signal suppression, and 3 axial sections per liver were obtained. Male Sprague-Dawley rats were scanned at baseline (n=32), and on day-3 (n=13), day-5 (n=11), day-7 (n=10), day-10 (n=4) respectively after BDL. Hematoxylin-eosin (HE) and picrosirius red staining liver histology was obtained at these time points.

RESULTS

The physiological liver parenchyma T1ρ was 38.38±1.53 msec (range, 36.05-41.53 msec). Liver T1ρ value elevated progressively after BDL. On day-10 after BDL all experimental animals can be separated from normal liver based on T1ρ measurement with lowest value being 42.82 msec. Day-7 and day-10 liver resembled METAVIR stage-F1/F2 fibrosis, and fibrous area counted for 0.22%±0.13% and 0.38%±0.44% of liver parenchyma area, respectively.

CONCLUSIONS

This study provides the first proof-of-principle that T1ρ might diagnose early stage liver fibrosis.

Comparison of T2(*) mapping with diffusion-weighted imaging in the characterization of low-grade vs intermediate-grade and high-grade prostate cancer

OBJECTIVE

To evaluate the diagnostic value of T2(*) mapping compared with apparent diffusion coefficient (ADC) mapping in the characterization of low-grade (Gleason score, ≤6) vs intermediate-grade and high-grade (Gleason score ≥7) prostate cancer (PCa).

METHODS

62 patients who underwent MRI before prostatectomy were evaluated. Two readers independently scored the probabilities of tumours in 12 regions of the prostate on T2(*) and ADC images. The data were divided into two groups, i.e. low- vs intermediate- and high-grade PCa, and correlated with the histopathological results. The diagnostic performance parameters, areas under the receiver-operating characteristic curves and interreader agreements were calculated.

RESULTS

For Reader 2, ADC mapping exhibited a greater accuracy for intermediate-grade PCas than for high-grade PCas (0.77 vs 0.83, p < 0.05). For both readers, T2(*) mapping exhibited a greater accuracy for intermediate-grade PCas than for high-grade PCas (Reader 1, 0.86 vs 0.81; Reader 2, 0.83 vs 0.78; p < 0.05). The areas under the curve of T2(*) mappings were greater than those of the ADC mappings for the intermediate- and high-grade PCas (Reader 1, 0.83 vs 0.78; Reader 2, 0.80 vs 0.75; p < 0.05) but not for the low-grade PCas (Reader 1, 0.86 vs 0.84; Reader 2, 0.83 vs 0.82; p > 0.05). The weighted κ value of T2(*) mapping was 0.59.

CONCLUSION

T2(*) mapping improves the accuracy of the characterization of intermediate- and high-grade PCas but not low-grade PCas compared with ADC mapping.

ADVANCES IN KNOWLEDGE

T2(*) mapping exhibited greater diagnostic accuracy than ADC mapping in the characterization of intermediate- and high-grade PCas. T2(*) mapping exhibited limited value in the characterization of low-grade PCa.

The Role of Diffusion-Weighted Imaging (DWI) in Locoregional Therapy Outcome Prediction and Response Assessment for Hepatocellular Carcinoma (HCC): The New Era of Functional Imaging Biomarkers

Reliable response criteria are critical for the evaluation of therapeutic response in hepatocellular carcinoma (HCC). Current response assessment is mainly based on: (1) changes in size, which is at times unreliable and lag behind the result of therapy; and (2) contrast enhancement, which can be difficult to quantify in the presence of benign post-procedural changes and in tumors presenting with a heterogeneous pattern of enhancement. Given these challenges, functional magnetic resonance imaging (MRI) techniques, such as diffusion-weighted imaging (DWI) have been recently investigated, aiding specificity to locoregional therapy response assessment and outcome prediction. Briefly, DWI quantifies diffusion of water occurring naturally at a cellular level (Brownian movement), which is restricted in multiple neoplasms because of high cellularity. Disruption of cellular integrity secondary to therapy results in increased water diffusion across the injured membranes. This review will provide an overview of the current literature on DWI therapy response assessment and outcome prediction in HCC following treatment with locoregional therapies.

Assessment of Musculoskeletal Malignancies with Functional MR Imaging

Functional MR imaging is the technique of choice to evaluate and manage malignant musculoskeletal masses. Advanced MR imaging sequences include chemical shift MR imaging, diffusion-weighted imaging with apparent diffusion coefficient mapping, MR spectroscopy imaging, and dynamic contrast-enhanced perfusion imaging. Functional MR imaging adds value to morphologic sequences in the detection, characterization, staging, and posttherapy assessment of malignant musculoskeletal malignancies. This article reviews the technical role of each functional sequence and their clinical applications to allow more confident decisions to be made. Multiparametric analysis of functional and anatomic MR sequences allows musculoskeletal tumors analysis to be improved.