Diffusion-weighted magnetic resonance imaging of the pancreas: diagnostic benefit from an intravoxel incoherent motion model-based 3 b-value analysis. Invest Radiol. 2014;49:93-100. [PMID: 24089021 DOI: 10.1097/rli.0b013e3182a71cc3]

Pancreatic Intraepithelial Neoplasia Revealed by Diffusion-Tensor MRI

OBJECTIVES

Detecting premalignant lesions for pancreatic ductal adenocarcinoma, mainly pancreatic intraepithelial neoplasia (PanIN), is critical for early diagnosis and for understanding PanIN biology. Based on PanIN's histology, we hypothesized that diffusion tensor imaging (DTI) and T2* could detect PanIN.

MATERIALS AND METHODS

DTI was explored for the detection and characterization of PanIN in genetically engineered mice (KC, KPC). Following in vivo DTI, ex vivo ultrahigh-field (16.4 T) MR microscopy using DTI, T2* was performed with histological validation. Sources of MR contrasts and histological features were investigated, including histological scoring for disease burden (lesion span) and severity (adjusted score). To test if findings in mice can be translated to humans, human pancreas specimens were imaged.

RESULTS

DTI detected PanIN and pancreatic ductal adenocarcinoma in vivo (6 KPC, 4 KC, 6 controls) with high discriminative ability: fractional anisotropy (FA) and radial diffusivity with area under the curve = 0.983 (95% confidence interval: 0.932-1.000); mean diffusivity and axial diffusivity (AD) with area under the curve = 1 (95% confidence interval: 1.000-1.000). MR microscopy with histological correlation (20 KC/KPC; 5 controls) revealed that sources of MR contrasts likely arise from microarchitectural signatures: high FA, AD in fibrotic areas surrounding lesions, high diffusivities within cysts, and high T2* within lesions' stroma. The strongest histological correlations for lesion span and adjusted score were obtained with AD (R = 0.708, P < 0.001; R = 0.789, P < 0.001, respectively). Ex vivo observations in 5 human pancreases matched our findings in mice, revealing substantial contrast between PanIN and normal pancreas.

CONCLUSIONS

DTI and T2* are useful for detecting and characterizing PanIN in genetically engineered mice and in the human pancreas, especially with AD and FA. These are encouraging findings for future clinical applications of pancreatic imaging.

Quantitative Magnetic Resonance Imaging for the Pancreas: Current Status

ABSTRACT

Magnetic resonance imaging (MRI) is important for evaluating pancreatic disorders, and anatomical landmarks play a major role in the interpretation of results. Quantitative MRI is an effective diagnostic modality for various pathologic conditions, as it allows the investigation of various physical parameters. Recent advancements in quantitative MRI techniques have significantly improved the accuracy of pancreatic MRI. Consequently, this method has become an essential tool for the diagnosis, treatment, and monitoring of pancreatic diseases. This comprehensive review article presents the currently available evidence on the clinical utility of quantitative MRI of the pancreas.

Quantitative Edge Analysis of Pancreatic Margins in Patients with Chronic Pancreatitis: A Correlation with Exocrine Function

BACKGROUND

Many efforts have been made to improve accuracy and sensitivity in diagnosing chronic pancreatitis (CP), obtaining quantitative assessments related to functional data. Our purpose was to correlate a computer-assisted analysis of pancreatic morphology, focusing on glandular margins, with exocrine function-measured by fecal elastase values-in chronic pancreatitis patients.

METHODS

We retrospectively reviewed chronic pancreatitis patients who underwent fecal elastase assessment and abdominal MRI in our institute within 1 year. We identified 123 patients divided into three groups based on the fecal elastase value: group A with fecal elastase > 200 μg/g; group B with fecal elastase between 100 and 200 μg/g; and group C with fecal elastase < 100 μg/g. Computer-assisted quantitative edge analysis of pancreatic margins was made on non-contrast-enhanced water-only Dixon T1-weighted images, obtaining the pancreatic margin score (PMS). PMS values were compared across groups using a Kruskal-Wallis test and the correlation between PMS and fecal elastase values was tested with the Spearman's test.

RESULTS

A significant difference in PMS was observed between the three groups (p < 0.0001), with a significant correlation between PMS and elastase values (r = 0.6080).

CONCLUSIONS

Quantitative edge analysis may stratify chronic pancreatitis patients according to the degree of exocrine insufficiency, potentially contributing to the morphological and functional staging of this pathology.

Simplified intravoxel incoherent motion DWI for differentiating malignant from benign breast lesions

Background

To evaluate simplified intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for differentiating malignant versus benign breast lesions as (i) stand-alone tool and (ii) add-on to dynamic contrast-enhanced magnetic resonance imaging.

Methods

1.5-T DWI data (b = 0, 50, 250, 800 s/mm²) were retrospectively analysed for 126 patients with malignant or benign breast lesions. Apparent diffusion coefficient (ADC) ADC (0, 800) and IVIM-based parameters D₁′ = ADC (50, 800), D₂′ = ADC (250, 800), f₁′ = f (0, 50, 800), f₂′ = f (0, 250, 800) and D*′ = D* (0, 50, 250, 800) were voxel-wise calculated without fitting procedures. Regions of interest were analysed in vital tumour and perfusion hot spots. Beside the single parameters, the combined use of D₁′ with f₁′ and D₂′ with f₂′ was evaluated. Lesion differentiation was investigated for lesions (i) with hyperintensity on DWI with b = 800 s/mm² (n = 191) and (ii) with suspicious contrast-enhancement (n = 135).

Results

All lesions with suspicious contrast-enhancement appeared also hyperintense on DWI with b = 800 s/mm². For task (i), best discrimination was reached for the combination of D₁′ and f₁′ using perfusion hot spot regions-of-interest (accuracy 93.7%), which was higher than that of ADC (86.9%, p = 0.003) and single IVIM parameters D₁′ (88.0%) and f₁′ (87.4%). For task (ii), best discrimination was reached for single parameter D₁′ using perfusion hot spot regions-of-interest (92.6%), which were slightly but not significantly better than that of ADC (91.1%) and D₂′ (88.1%). Adding f₁′ to D₁′ did not improve discrimination.

Conclusions

IVIM analysis yielded a higher accuracy than ADC. If stand-alone DWI is used, perfusion analysis is of special relevance.

Simplified intravoxel incoherent motion diffusion-weighted MRI of liver lesions: feasibility of combined two-colour index maps

Background

To evaluate the feasibility of two-colour index maps containing combined diffusion and perfusion information from simplified intravoxel incoherent motion (IVIM) for liver lesion malignancy assessment.

Methods

Diffusion-weighted data from a respiratory-gated 1.5-T magnetic resonance sequence were analysed in 109 patients with liver lesions. With three b values (0, 50, 800 s/mm²) estimated diffusion coefficient D′, perfusion fraction f′, and apparent diffusion coefficient (ADC) maps were calculated and analysed for regions of interest (ROIs). D′ and f′ cutoff values were determined by differentiating haemangiomas from other lesions and focal nodular hyperplasias from other lesions, respectively. Combined I_Df index maps were generated with a voxel value set to 100, if both D′ and f′ voxel values were lower than their cutoff values (1,529.4 × 10^-6 mm²/s and 114.4 × 10^-3, respectively), otherwise to 0. Moreover, I_ADC index maps were generated from ADC cutoff value (1,338.5 × 10^-6 mm²/s) obtained by differentiating benign from malignant lesions. Discriminatory power was assessed for both I_Df and I_ADC. Index maps were displayed as two-colour overlays to b-800 images and visually assessed within the translucent hyperintense areas.

Results

For I_Df, the same diagnostic accuracy was achieved as for the combined use of parameters D′ and f′ (93.6%). Compared to I_ADC, I_Df showed a higher diagnostic accuracy. Visual judgment of I_Df yielded an accuracy (95.4%) similar to that of quantitative analysis (93.6%).

Conclusion

Voxel-wise combined two-colour index maps I_Df provide similar diagnostic accuracy as ROI-based combination of estimated IVIM parameters D′ and f′ and are suitable for visual assessment of liver lesion malignancy.

Accuracy of quantitative diffusion-weighted imaging for differentiating benign and malignant pancreatic lesions: a systematic review and meta-analysis

BACKGROUND

A variety of imaging techniques can be used to evaluate diffusion characteristics to differentiate malignant and benign pancreatic lesions. The diagnostic performance of diffusion parameters has not been systematic assessed.

PURPOSE

We aimed to investigate the diagnostic efficacy of quantitative diffusion-weighted imaging (DWI) for pancreatic lesions.

METHODS

A literature search was conducted using the PubMed, Embase, and Cochrane Library databases for studies from inception to March 30, 2020, which involves the quantitative diagnostic performance of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) in the pancreas. Studies were reviewed according to inclusion and exclusion criteria. The quality of articles was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 (QUATAS-2). A bivariate random-effects model was used to evaluate pooled sensitivities and specificities. Univariable meta-regression analysis was used to test the effects of factors that contributed to the heterogeneity.

RESULTS

A total of 31 studies involving 1558 patients were ultimately eligible for data extraction. The lowest heterogeneity was found in specificity of perfusion fraction (f) with the I² value was 17.97% and Cochran p value was 0.28. However, high heterogeneities were found for the other parameters (all I² > 50%). There was no publication bias found in funnel plot (p = 0.30) for the apparent diffusion coefficient (ADC) parameter. The pooled sensitivities for ADC, f, pure diffusion coefficient (D), and pseudo diffusivity coefficient (D*) were 83%, 81%, 76%, and 84%, respectively. The pooled specificities for ADC, f, D, and D* were 87%, 83%, 69%, and 81% respectively. The areas under the curves for ADC, f, D, and D* were 0.92, 0.87, 0.79, and 0.87 respectively.

CONCLUSION

Quantitative DWI and IVIM have a good diagnostic performance for differentiating malignant and benign pancreatic lesions.

KEY POINTS

• IVIM has high sensitivity and specificity (84% and 83%, respectively) for differential diagnosis of pancreatic lesions, which is comparable to that of the ADC (83% and 87%, respectively). • The ADC has an excellent diagnostic performance for differentiating malignant from benign IPMNs (sensitivity, 0.83; specificity, 0.92); the f has the best diagnostic performance for differentiating pancreatic carcinoma from PNET (sensitivity, 0.85; specificity, 0.85). • For the ADC, using a maximal b value < 800 s/mm² has a higher diagnostic accuracy than ≥ 800 s/mm²; performing in a high field strength (3.0 T) system has a higher diagnostic accuracy than a low field strength (1.5 T) for pancreatic lesions.

Diagnostic performance of diffusion MRI for pancreatic ductal adenocarcinoma characterisation: A meta-analysis

PURPOSE

To assess the diagnostic performance of intravoxel incoherent motion (IVIM) and diffusion-weighted imaging (DWI) for characterising pancreatic ductal adenocarcinoma (PDAC).

METHOD

A literature search was performed through PubMed, Web of Science, the Cochrane Library, and Embase databases. The search date was updated to extend until 28 October 2020, with no starting time limitation. The pooled sensitivity and specificity were calculated using a bivariate random effects model. Summary receiver operating characteristic curves were constructed, and area under the curve (AUC) of each diffusion parameter was calculated. Subgroup and meta-regression analyses were performed to assess for heterogeneity. Study quality was assessed.

RESULTS

Twenty-nine studies involving 1579 participants were included, of which 26 evaluated the apparent diffusion coefficient (ADC) and eight evaluated IVIM, with five evaluating both ADC and IVIM. Pooled sensitivity and specificity of ADC were 83 % (95 % CI, 76 %-88 %, I² = 86 %) and 85 % (95 % CI, 79 %-90 %, I² = 77 %), respectively, and AUC was 0.91 (95 % CI, 0.88-0.93). The perfusion fraction had the highest diagnostic accuracy in the IVIM model; the pooled sensitivity, specificity, and AUC were 87 % (95 % CI, 81 %-92 %, I² = 45 %), 88 % (95 % CI, 77 %-94 %, I² = 57 %), and 0.93 (95 % CI, 0.91-0.95), respectively. The pooled sensitivity, specificity and AUC for the tissue diffusion coefficient were 74 % (95 % CI, 55 %-87 %, I² = 87 %), 69 % (95 % CI, 52 %-82 %, I² = 73 %), and 0.77 (95 % CI, 0.73-0.81), respectively. And the pooled sensitivity, specificity, and AUC for the pseudodiffusion coefficient were 89 % (95 % CI, 77 %-96 %, I² = 79 %), 74 % (95 % CI, 60 %-84 %, I² = 78 %), and 0.88(95 %CI,0.85-0.91), respectively. Meta-regression analyses revealed that study design (specificity, P＜0.01), region-of-interest delineation (sensitivity, P = 0.02;specificity, P = 0.03), field strength (sensitivity, P＜0.01), and thickness (sensitivity, P＜0.01; specificity, P = 0.01) were sources of ADC heterogeneity.

CONCLUSIONS

DWI and IVIM have comparable diagnostic power and good diagnostic performance for characterising PDAC.

Associations between IVIM histogram parameters and histopathology in rectal cancer

PURPOSE

Histogram analysis can better reflect tumor heterogeneity than conventional imaging analysis. The present study analyzed possible correlations between histogram analysis parameters derived from Intravoxel-incoherent imaging (IVIM) and histopathological features in rectal cancer (RC).

METHODS

Seventeen patients with histopathologically proven rectal adenocarcinomas were retrospectively acquired. In all cases, pelvic MRI was performed. Diffusion weighted imaging was obtained using a multi-slice single-shot echo-planar imaging sequence with b values of 0, 50, 200, 500 and 1000 s/mm². Simplified IVIM analysis was performed using the IntelliSpace portal, version 10 and the following images were generated: f (perfusion fraction) map, D (true diffusion coefficient) map, and ADC map utilizing all b-values. Histogram based analysis of signal intensities was performed for every IVIM map using an in-house matlab tool. Histopathology was investigated using Ki 67 specimens with calculation of Ki 67-index and cellularity. CD31 stained specimens were used for calculation of microvessel density (MVD).

RESULTS

There were statistically significant correlations between Ki 67 index and mode derived from ADC as well as entropy from f, r=-0.50, p=.04 and r=-0.55, p=.02, respectively. MVD correlated well with parameters derived from f.

CONCLUSION

IVIM histogram analysis parameters can reflect histopathology in RC. ADC and D values are associated with proliferation potential. Perfusion fraction f is associated with MVD.

New Advances in Magnetic Resonance Techniques in Abdomen and Pelvis

This article explores new acquisition methods in magnetic resonance (MR) imaging to provide high spatial and temporal resolution imaging for a wide spectrum of clinical applications in the abdomen and pelvis. We present an overview of some of these advanced MR techniques, such as non-cartesian image acquisition, fast sampling and compressed sensing, diffusion quantification and quantitative MR that can improve data sampling, enhance image quality, yield quantitative measurements, and/or optimize diagnostic performance in the body.

Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends

Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.

B-Value Optimization in the Estimation of Intravoxel Incoherent Motion Parameters in Patients with Cervical Cancer

OBJECTIVE

This study aimed to find the optimal number of b-values for intravoxel incoherent motion (IVIM) imaging analysis, using simulated and in vivo data from cervical cancer patients.

MATERIALS AND METHODS

Simulated data were generated using literature pooled means, which served as reference values for simulations. In vivo data from 100 treatment-naïve cervical cancer patients with IVIM imaging (13 b-values, scan time, 436 seconds) were retrospectively reviewed. A stepwise b-value fitting algorithm calculated optimal thresholds. Feed forward selection determined the optimal subsampled b-value distribution for biexponential IVIM fitting, and simplified IVIM modeling using monoexponential fitting was attempted. IVIM parameters computed using all b-values served as reference values for in vivo data.

RESULTS

In simulations, parameters were accurately estimated with six b-values, or three b-values for simplified IVIM, respectively. In vivo data showed that the optimal threshold was 40 s/mm² for patients with squamous cell carcinoma and a subsampled acquisition of six b-values (scan time, 198 seconds) estimated parameters were not significantly different from reference parameters (individual parameter error rates of less than 5%). In patients with adenocarcinoma, the optimal threshold was 100 s/mm², but an optimal subsample could not be identified. Irrespective of the histological subtype, only three b-values were needed for simplified IVIM, but these parameters did not retain their discriminative ability.

CONCLUSION

Subsampling of six b-values halved the IVIM scan time without significant losses in accuracy and discriminative ability. Simplified IVIM is possible with only three b-values, at the risk of losing diagnostic information.

Dynamic Contrast-Enhanced MRI for Measuring Pancreatic Perfusion in Acute Pancreatitis: A Preliminary Study

RATIONALE AND OBJECTIVES

To assess the characteristics of pancreatic perfusion in normal pancreas and acute pancreatitis (AP) by using dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI).

METHOD AND MATERIALS

Eighty-One AP patients and 26 normal subjects underwent DCE-MRI. The Omitk-Tool was used to analyze perfusion parameters such as K^trans, V_p^, and AUC. The parameters of pancreas between AP and control groups were compared. In AP patients, the parameters were compared between edematous and necrotizing pancreatitis and among different grades of AP as determined by MR severity index (MRSI) and the 2012 Revised Atlanta Classification of AP.

RESULTS

The K^trans, V_p^, and AUC values of AP were lower than those of the control group (p = 0.007, 0.000, and 0.025). According to MRSI, the K^trans and AUC values were significantly different between mild and moderate (p = 0.000, 0.000) and between mild and severe (p = 0.008, 0.016) AP but not between moderate and severe AP (p = 0.218, 0.217). Based on the 2012 Revised Atlanta Classification, the K^trans values were significantly different between mild and moderately severe (p = 0.000) and between mild and severe (p = 0.005) AP, but not between moderately severe and severe AP (p = 0.619). The K^trans values were significantly different between edematous and necrotizing pancreatitis (p = 0.03).

CONCLUSION

The application of DCE-MRI to evaluate pancreatic perfusion contributes to the diagnosis of AP and its severity grade. Pancreatic perfusion is lower in AP patients than in patients with a normal pancreas, and pancreatic perfusion tends to decrease as the severity of AP increases.

Exploratory Study of Apparent Diffusion Coefficient Histogram Metrics in Assessing Pancreatic Malignancy

PURPOSE

To evaluate whole-lesion 3D-histogram apparent diffusion coefficient (ADC) metrics for assessment of pancreatic malignancy.

METHODS

Forty-two pancreatic malignancies (36 pancreatic adenocarcinoma [PDAC], 6 pancreatic neuroendocrine [PanNET]) underwent abdominal magnetic resonance imaging (MRI) with diffusion-weighted imaging before endoscopic ultrasound biopsy or surgical resection. Two radiologists independently placed 3D volumes of interest to derive whole-lesion histogram ADC metrics. Mann-Whitney tests and receiver operating characteristic analyses were used to assess metrics' diagnostic performance for lesion histology, T-stage, N-stage, and grade.

RESULTS

Whole-lesion ADC histogram metrics lower in PDACs than PanNETs for both readers (P ≤ .026) were mean ADC (area under the curve [AUC] = 0.787-0.792), mean of the bottom 10th percentile (mean_0-10) (AUC = 0.787-0.880), mean of the 10th-25th percentile (mean_10-25) (AUC = 0.884-0.917) and mean of the 25th-50th percentile (mean_25-50) (AUC = 0.829-0.829). For mean_10-25 (metric with highest AUC for identifying PDAC), for reader 1 a threshold > 0.94 × 10^-3 mm²/s achieved sensitivity 94% and specificity 83%, and for reader 2 a threshold > 0.82 achieved sensitivity 97% and specificity 67%. Metrics lower in nodal status ≥ N₁ than N₀ for both readers (P ≤ .043) were mean_0-10 (AUC = 0.789-0.822) and mean_10-25 (AUC = 0.800-0.822). For mean_10-25 (metric with highest AUC for identifying N₀), for reader 1 a threshold <1.17 achieved sensitivity 87% and specificity 67%, and for reader 2 a threshold <1.04 achieved sensitivity 87% and specificity 83%. No metric was associated with T-stage (P > .195) or grade (P > .215).

CONCLUSION

Volumetric ADC histogram metrics may serve as non-invasive biomarkers of pancreatic malignancy. Mean_10-25 outperformed standard mean for lesion histology and nodal status, supporting the role of histogram analysis.

Quantitative pancreatic MRI: a pathology-based review

MRI plays an important role in the clinical management of pancreatic disorders and interpretation is reliant on qualitative assessment of anatomy. Conventional sequences capturing pancreatic structure can however be adapted to yield quantitative measures which provide more diagnostic information, with a view to increasing diagnostic accuracy, improving patient stratification, providing robust non-invasive outcome measures for therapeutic trials and ultimately personalizing patient care. In this review, we evaluate the use of established techniques such as secretin-enhanced MR cholangiopancreatography, diffusion-weighted imaging, T ₁, T ₂* and fat fraction mapping, but also more experimental methods such as MR elastography and arterial spin labelling, and their application to the assessment of diffuse pancreatic disease (including chronic, acute and autoimmune pancreatitis/IgG4 disease, metabolic disease and iron deposition disorders) and cystic/solid focal pancreatic masses. Finally, we explore some of the broader challenges to their implementation and future directions in this promising area.

Intravoxel incoherent motion diffusion-weighted imaging for assessment of histologic grade of hepatocellular carcinoma: comparison of three methods for positioning region of interest

OBJECTIVES

To prospectively compare the diagnostic performances of three methods of region of interest (ROI) placement for the measurements of intravoxel incoherent motion (IVIM) diffusion-weighted MR imaging in differentiating the histologic grade of hepatocellular carcinoma (HCC).

METHODS

Eighty-seven patients with 91 newly diagnosed HCCs were studied using IVIM imaging. Two attending radiologists separately identified the selection of tumour tissue for ROI positioning. Three different ROI positioning methods, namely the whole tumour volume (WTV) method, three-ROI method and one-section method, were used for the measurement. Kruskal-Wallis rank test or one-way ANOVA was used to compare the difference in IVIM parameters and ADC across the three different ROI positioning methods. Spearman correlation analysis was used to determine the correlation between each parameter and Edmondson-Steiner (E-S) grade. Receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic performance.

RESULTS

For the ADC and ADC_slow, the mean value measured by using the WTV method was significant higher than the one-section and three-ROI methods (all p < 0.01). For the ADC_slow, the highest area under curve (AUC) with a value of 0.969 was obtained by using the WTV method, followed by the one-section method (AUC = 0.938) and three-ROI method (AUC = 0.873). Additionally, for the ADC, AUC values were 0.861 for WTV method, 0.840 for one-section method and 0.806 for three-ROI method.

CONCLUSIONS

Different ROI positioning methods used significantly affect the IVIM parameters and ADC measurements. Measurements of ADC_slow value derived from WTV method entailed the highest diagnostic performance in grading HCC.

KEY POINTS

• Diffusion MRI is useful for non-invasively differentiating the histologic grade of hepatocellular carcinoma. • Different ROI positioning methods used significantly affect the IVIM parameters and ADC measurements. • IVIM model is advantageous over mono-exponential model for assessing the histologic grade of hepatocellular carcinoma.

Diffusion kurtosis imaging and conventional diffusion weighted imaging to assess electrochemotherapy response in locally advanced pancreatic cancer

Background The aim of the study was to evaluate diagnostic performance of functional parameters derived by conventional mono-exponential approach of diffusion weighted imaging (DWI) and by diffusion kurtosis imaging (DKI) in the assessment of pancreatic tumours treated with electrochemotherapy (ECT). Patients and methods Twenty-one consecutive patients with locally advanced pancreatic adenocarcinoma subjected to ECT were enrolled in a clinical approved trial. Among twenty-one enrolled patients, 13/21 (61.9%) patients were subjected to MRI before and after ECT. DWI was performed with a 1.5 T scanner; a free breathing axial single shot echo planar DWI pulse sequence parameters were acquired using seven b value = 0, 50, 100, 150, 400, 800, 1000 s/mm2. Apparent diffusion coefficient by conventional mono-exponential approach and mean of diffusion coefficient (MD) and mean of diffusional kurtosis (MK) by DKI approach were derived from DWI. Receiver operating characteristic (ROC) analysis was performed and sensitivity, specificity, positive and negative predictive value were calculated. Results Among investigated diffusion parameters, only the MD derived by DKI showed a significant variation of values between pre and post treatment (p = 0.02 at Wilcoxon test) and a significant statistically difference for percentage change between responders and not responders (p = 0.01 at Kruskal Wallis test). MD had a good diagnostic performance with a sensitivity of 80%, a specificity of 100% and area under ROC of 0.933. Conclusions MD derived by DKI allows identifying responders and not responders patients subject to ECT treatment. MD had higher diagnostic performance to assess ECT response compared to conventional DWI derived parameters.

Whole-tumor histogram analysis of non-Gaussian distribution DWI parameters to differentiation of pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas

PURPOSE

To evaluate the utility of volumetric histogram analysis of monoexponential and non-Gaussian distribution DWI models for discriminating pancreatic ductal adenocarcinoma (PDAC) and neuroendocrine tumor (pNET).

MATERIALS AND METHODS

A total of 340 patients were retrospectively reviewed. Finally, 62 patients with histopathological confirmed PDAC (n = 42) and pNET (n = 20) were enrolled in the study. All the patients accepted magnetic resonance imaging (MRI) at 3 T (including multi-b value DWI, 0-1000 s/mm2). Isotropic apparent diffusion coefficient (ADC), true molecular diffusion (Dt), perfusion-related diffusion (Dp), perfusion fraction (f), distributed diffusion coefficient (DDC) and alpha (α) were obtained from different DWI models. Then, mean value, median value, 10th and 90th percentiles were obtained from histogram analysis of each DWI parameter.

RESULTS

Histogram metrics derived from ADC, Dp, f and DDC were significantly lower in PDAC than pNET group (P < 0.05). In contrast, histogram metrics derived from α were observed significantly higher in the PDAC than pNET group (P < 0.05). No significant difference was found in Dt (P ≥ 0.05) between PDAC and pNET patients. Among all parameters, f-median had the highest diagnostic performance (AUC 0.91, cutoff value 0.188, sensitivity 97.62%, specificity 80%).

CONCLUSIONS

f-Median derived from IVIM DWI model may be potentially more valuable parameter than ADC, Dp, DDC and α for discriminating PDAC and pNET. Histogram analysis based on the entire tumor was an emerging and valuable tool.

Early assessment of acute kidney injury using targeted field of view diffusion-weighted imaging: An in vivo study

Acute kidney injury (AKI) is a common complication in various clinical settings. In recent years, AKI diagnostics have been investigated intensively showing the emerging need for early characterization of this disease. To verify whether targeted field-of-view diffusion-weighted imaging (tFOV-DWI) is feasible to significantly improve the performance of traditional full field-of-view diffusion-weighted imaging (fFOV-DWI) in the early assessment of AKI. 14 rabbits with unilateral AKI were induced by injection of microspheres under the guidance of digital subtraction angiography (DSA). All rabbits underwent tFOV-DWI and fFOV-DWI immediately after the surgery. Artifacts, distortion and lesion identification were graded by two experienced radiologists, and the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured. Apparent diffusion coefficient (ADC) maps were then derived. Blood samples were collected pre- and post-surgery and serum creatinine weres measured. Renal specimen and biopsy were performed as the reference standard. Student t-test was used to ascertain statistical significance between the above parameters for tFOV-DWI and fFOV-DWI. The interobserver agreement and ADC measurements agreement were assessed. A higher percentage of renal lesions (17 out of 19) were detected in tFOV-DWI compared with fFOV-DWI (14 out of 19). Significant differences were observed in ADC value for both techniques between the lesion regions and normal tissues (p < 0.001). Histological findings were inversely correlated with ADC values of tFOV-DWI (r = -0.97, P < 0.001 for cortex; r = -0.98, P < 0.001 for medulla) and fFOV-DWI sequences (r = -0.95, P < 0.001 for cortex; r = -0.98, P < 0.001 for medulla). Those tFOV-DW images rated by the radiologists exhibit superior performance in terms of all assessed measures (P < 0.05), and interobserver agreement was excellent (ICC, 0.78 to 0.92). Besides, the ADC values derived from tFOV-DWI had a satisfactory agreement with those estimated by fFOV-DWI. The animal study demonstrates that the tFOV-DWI strategy provided visually better image quality and lesion depiction than conventional fFOV-DWI for early assessment of AKI.

Imaging biomarkers in oncology: Basics and application to MRI

Cancer remains a global killer alongside cardiovascular disease. A better understanding of cancer biology has transformed its management with an increasing emphasis on a personalized approach, so-called "precision cancer medicine." Imaging has a key role to play in the management of cancer patients. Imaging biomarkers that objectively inform on tumor biology, the tumor environment, and tumor changes in response to an intervention complement genomic and molecular diagnostics. In this review we describe the key principles for imaging biomarker development and discuss the current status with respect to magnetic resonance imaging (MRI).

LEVEL OF EVIDENCE

5 TECHNICAL EFFICACY: Stage 5 J. Magn. Reson. Imaging 2018;48:13-26.

Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging for predicting histological grade of hepatocellular carcinoma: Comparison with conventional diffusion-weighted imaging

AIM

To compare intravoxel incoherent motion (IVIM)-derived parameters with conventional diffusion-weighted imaging (DWI) parameters in predicting the histological grade of hepatocellular carcinoma (HCC) and to evaluate the correlation between the parameters and the histological grades.

METHODS

A retrospective study was performed. Sixty-two patients with surgically confirmed HCCs underwent diffusion-weighted magnetic resonance imaging with twelve b values (10-1200 s/mm²). The apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) were calculated by two radiologists. The IVIM and conventional DWI parameters were compared among the different grades by using analysis of variance (ANOVA) and the Kruskal-Wallis test. Receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic efficiency of distinguishing between low-grade (grade 1, G1) and high-grade (grades 2 and 3, G2 and G3) HCC. The correlation between the parameters and the histological grades was assessed by using the Spearman correlation test. Bland-Altman analysis was used to evaluate the reproducibility of the two radiologists’ measurements.

RESULTS

The differences in the ADC and D values among the groups with G1, G2, and G3 histological grades of HCCs were statistically significant (P < 0.001). The D* and f values had no significant differences among the different histological grades of HCC (P > 0.05). The ROC analyses demonstrated that the D and ADC values had better diagnostic performance in differentiating the low-grade HCC from the high-grade HCC, with areas under the curve (AUCs) of 0.909 and 0.843, respectively, measured by radiologist 1 and of 0.911 and 0.852, respectively, measured by radiologist 2. The following significant correlations were obtained between the ADC, D, and D* values and the histological grades: r = -0.619 (P < 0.001), r = -0.628 (P < 0.001), and r = -0.299 (P = 0.018), respectively, as measured by radiologist 1; r = -0.622 (P < 0.001), r = -0.633 (P < 0.001), and r = -0.303 (P = 0.017), respectively, as measured by radiologist 2. The intra-class correlation coefficient (ICC) values between the two observers were 0.996 for ADC, 0.997 for D, 0.996 for D*, and 0.992 for f values, which indicated excellent inter-observer agreement in the measurements between the two observers.

CONCLUSION

The IVIM-derived D and ADC values show better diagnostic performance in differentiating high-grade HCC from low-grade HCC, and there is a moderate to good correlation between the ADC and D values and the histological grades.

Relative enhanced diffusivity: noise sensitivity, protocol optimization, and the relation to intravoxel incoherent motion

OBJECTIVE

To explore the relationship between relative enhanced diffusivity (RED) and intravoxel incoherent motion (IVIM), as well as the impact of noise and the choice of intermediate diffusion weighting (b value) on the RED parameter.

MATERIALS AND METHODS

A mathematical derivation was performed to cast RED in terms of the IVIM parameters. Noise analysis and b value optimization was conducted by using Monte Carlo calculations to generate diffusion-weighted imaging data appropriate to breast and liver tissue at three different signal-to-noise ratios.

RESULTS

RED was shown to be approximately linearly proportional to the IVIM parameter f, inversely proportional to D and to follow an inverse exponential decay with respect to D*. The choice of intermediate b value was shown to be important in minimizing the impact of noise on RED and in maximizing its discriminatory power. RED was shown to be essentially a reparameterization of the IVIM estimates for f and D obtained with three b values.

CONCLUSION

RED imaging in the breast and liver should be performed with intermediate b values of 100 and 50 s/mm², respectively. Future clinical studies involving RED should also estimate the IVIM parameters f and D using three b values for comparison.

Intravoxel incoherent motion MRI as a means to measure in vivo perfusion: A review of the evidence

The idea that in vivo intravoxel incoherent motion magnetic resonance signal is influenced by blood motion in the microvasculature is exciting, because it suggests that local and quantitative perfusion information can be obtained in a simple and elegant way from a few diffusion-weighted images, without contrast injection. When the method was proposed in the late 1980s some doubts appeared as to its feasibility, and, probably because the signal to noise and image quality at the time was not sufficient, no obvious experimental evidence could be produced to alleviate them. Helped by the tremendous improvements seen in the last three decades in MR hardware, pulse design, and post-processing capabilities, an increasing number of encouraging reports on the value of intravoxel incoherent motion perfusion imaging have emerged. The aim of this article is to review the current published evidence on the feasibility of in vivo perfusion imaging with intravoxel incoherent motion MRI.

Chronic pancreatitis

Chronic pancreatitis is defined as a pathological fibro-inflammatory syndrome of the pancreas in individuals with genetic, environmental and/or other risk factors who develop persistent pathological responses to parenchymal injury or stress. Potential causes can include toxic factors (such as alcohol or smoking), metabolic abnormalities, idiopathic mechanisms, genetics, autoimmune responses and obstructive mechanisms. The pathophysiology of chronic pancreatitis is fairly complex and includes acinar cell injury, acinar stress responses, duct dysfunction, persistent or altered inflammation, and/or neuro-immune crosstalk, but these mechanisms are not completely understood. Chronic pancreatitis is characterized by ongoing inflammation of the pancreas that results in progressive loss of the endocrine and exocrine compartment owing to atrophy and/or replacement with fibrotic tissue. Functional consequences include recurrent or constant abdominal pain, diabetes mellitus (endocrine insufficiency) and maldigestion (exocrine insufficiency). Diagnosing early-stage chronic pancreatitis is challenging as changes are subtle, ill-defined and overlap those of other disorders. Later stages are characterized by variable fibrosis and calcification of the pancreatic parenchyma; dilatation, distortion and stricturing of the pancreatic ducts; pseudocysts; intrapancreatic bile duct stricturing; narrowing of the duodenum; and superior mesenteric, portal and/or splenic vein thrombosis. Treatment options comprise medical, radiological, endoscopic and surgical interventions, but evidence-based approaches are limited. This Primer highlights the major progress that has been made in understanding the pathophysiology, presentation, prevalence and management of chronic pancreatitis and its complications.

Modifications of pancreatic diffusion MRI by tissue characteristics: what are we weighting for?

Diffusion-weighted imaging holds the potential to improve the diagnosis and biological characterization of pancreatic disease, and in particular pancreatic cancer, which exhibits decreased values of the apparent diffusion coefficient (ADC). Yet, variable and overlapping ADC values have been reported for the healthy and the pathological pancreas, including for cancer and other benign conditions. This controversy reflects the complexity of probing the water-diffusion process in the pancreas, which is dependent upon multiple biological factors within this organ's unique physiological environment. In recent years, extensive studies have investigated the correlation between tissue properties including cellularity, vascularity, fibrosis, secretion and microstructure and pancreatic diffusivity. Understanding how the various physiological and pathological features and the underlying functional processes affect the diffusion measurement may serve to optimize the method for improved diagnostic gain. Therefore, the aim of the present review article is to elucidate the relationship between pancreatic tissue characteristics and diffusion MRI measurement.

Effect of region of interest size on ADC measurements in pancreatic adenocarcinoma

BACKGROUND

To investigate the influence of region of interest (ROI) size on tumor apparent diffusion coefficient (ADC) measurements in pancreatic cancer.

METHODS

The study population consisted of 64 patients with pathologically proved pancreatic ductal adenocarcinomas (PDACs), who underwent preoperative magnetic resonance imaging (MRI) examinations including diffusion-weighted imaging (DWI). The tumor ADCs were measured by two independent readers using six round ROIs with sizes ranging from 20 to 214 mm² (9 to 97 pixels) in both the six separate measurements. The intra- and inter-observer variabilities were analyzed by using the coefficient of variance (CV), the interclass correlation coefficient (ICC) and Bland-Altman analysis. The mean ADCs measured with the 6 different-sized ROIs were compared using one-way repeated analysis of variance. The sample sizes were calculated by using 80% power and a 5% significance level to detect 10 to 25% changes in ADC measurements.

RESULTS

The largest ROI (ROI₂₁₄) yielded the best intra-observer repeatability (CV, 6.3%; ICC, 0.93) and inter-observer reproducibility (CV, 10.1%; ICC, 0.84). The mean differences in ADC measurements ± limits of agreement between the two readers were (0.06 ± 0.47) × 10^-3 mm² for ROI₂₀, (0.08 ± 0.46) × 10^-3 mm² for ROI₄₆, (0.05 ± 0.37) × 10^-3 mm² for ROI₈₂, (0.07 ± 0.42) × 10^-3 mm² for ROI₁₁₅, (0.05 ± 0.43) × 10^-3 mm² for ROI₁₅₂ and (-0.02 ± 0.29) × 10^-3 mm² for ROI₂₁₄.

CONCLUSIONS

ROI size had a considerable influence on the ADC measurements of PDACs.

Intravoxel incoherent motion DWI of the pancreatic adenocarcinomas: monoexponential and biexponential apparent diffusion parameters and histopathological correlations

Background

To investigate the associations between the diffusion parameters obtained from multiple-b-values diffusion weighted imaging (DWI) of pancreatic ductal adenocarcinoma (PDAC) and the aggressiveness and local stage prediction, and assess the values of the quantitative parameters for the discrimination of tumors from healthy pancreas.

Methods

Fifty-one patients with surgical pathology-proven PDAC (size, 35 ± 12 mm) and fifty-seven healthy volunteers were enrolled. Diffusion parameters including monoexponential apparent diffusion coefficient (ADC_b and ADC_total) and biexponential intravoxel incoherent motion (IVIM) parameters (ADC_slow, ADC_fast and f) based on 9 b-values (0 to 1000s/mm²) DWI were calculated for the lesions and the healthy pancreas. These parameters were compared by grades of differentiation, lymph node status, tumor stage and location. The diagnostic performances were calculated and compared by using the receiver operating characteristic curves (ROC) analyses.

Results

There was no statistically significant difference in ADC_b, ADC_total, ADC_slow, ADC_fast or f between PDAC stage T1/T2 and stage T3/T4 or moderately differentiated versus poorly differentiated PDAC (p = 0.060-0.941). In addition, no significant differences were observed for the quantitative parameters between tumors located in the pancreatic head versus other pancreatic regions (p = 0.203-0.954) or between tumors with and without metastatic peri-pancreatic lymph nodes (p = 0.313-0.917). ADC_25-600, ADC₁₀₀₀, ADC_total and ADC_fast were significantly lower for PDAC compared the healthy pancreas (all p < 0.05). ROC analyses showed the area under curve for ADC₂₀ was the largest (0.911) to distinguish PDAC from normal pancreas (cut-off value, 5.58 × 10⁻³mm²/s) and had the highest combined sensitivity (89.5%) and specificity (82.4%).

Conclusions

Multiple-b-values DWI derived monoexponential and biexponential parameters of PDAC do not exhibit significance dependence on tumor grade or tumor characteristics. ADC₂₀ provided the best accuracy for differentiating PDAC from healthy pancreas in the study.

Diffusion tensor imaging in abdominal organs

Initially, diffusion tensor imaging (DTI) was mainly applied in studies of the human brain to analyse white matter tracts. As DTI is outstanding for the analysis of tissue´s microstructure, the interest in DTI for the assessment of abdominal tissues has increased continuously in recent years. Tissue characteristics of abdominal organs differ substantially from those of the human brain. Further peculiarities such as respiratory motion and heterogenic tissue composition lead to difficult conditions that have to be overcome in DTI measurements. Thus MR measurement parameters have to be adapted for DTI in abdominal organs. This review article provides information on the technical background of DTI with a focus on abdominal imaging, as well as an overview of clinical studies and application of DTI in different abdominal regions. Copyright © 2015 John Wiley & Sons, Ltd.

Diffusion-weighted MR imaging of the pancreas: optimizing b-value for visualization of pancreatic adenocarcinoma

OBJECTIVES

To determine the optimal b-value of 3.0-T diffusion-weighted imaging (DWI) for visualizing pancreatic adenocarcinomas

METHODS

Fifty-five patients with histologically confirmed pancreatic adenocarcinoma underwent DWI with different b-values (b = 500, 1000, 1500, and 2000 s/mm(2)) at 3.0 T. For each b-value, we retrospectively evaluated DWI findings of pancreatic adenocarcinomas (clear hyperintensity relative to the surrounding pancreas, hyperintensity with an unclear distal border, and isointensity) and image quality, and measured tumour-to-pancreas signal intensity (SI) ratios. DWI findings, image quality, and tumour-to-pancreas SI ratios were compared between the four b-values.

RESULTS

There was a significantly higher incidence of tumours showing clear hyperintensity on DWI with b-value of 1500 s/mm(2) than on that with b-value of 1000 s/mm(2) (P < 0.001), and on DWI with b-value of 1000 s/mm(2) than on that with b-value of 500 s/mm(2) (P < 0.001). The tumour-to-distal pancreas SI ratio was higher with b-value of 1500 s/mm(2) than with b-value of 1000 s/mm(2) (P < 0.001), and with b-value of 1000 s/mm(2) than with b-value of 500 s/mm(2) (P < 0.001). A lower image quality was obtained at increasing b-values (P < 0.001); the lowest scores were observed with b-value of 2000 s/mm(2).

CONCLUSIONS

The use of b = 1500 s/mm(2) for 3.0-T DWI can improve the delineation of pancreatic adenocarcinomas.

KEY POINTS

• Diffusion-weighted imaging (DWI) has been used for diagnosing pancreatic adenocarcinoma • The techniques for DWI, including the choice of b-values, vary considerably • DWI often fails to delineate pancreatic adenocarcinomas because of hyperintense pancreas • DWI with a higher b-value can improve the tumour delineation • The lowest image quality was obtained on DWI with b-value = 2000 s/mm (2).

A comparison of fitting algorithms for diffusion-weighted MRI data analysis using an intravoxel incoherent motion model

OBJECT

The objective of this study is to propose a modified VARiable PROjection (VARPRO) algorithm specifically tailored for fitting the intravoxel incoherent motion (IVIM) model to diffusion-weighted magnetic resonance imaging (DW-MRI) data from locally advanced rectal cancer (LARC).

MATERIALS AND METHODS

The proposed algorithm is compared with classical non-linear least squares (NLLS) analysis using the Levenberg-Marquardt (LM) algorithm and with two recently proposed algorithms for 'segmented' analysis. These latter two comprise two consecutive steps: first, a subset of parameters is estimated using a portion of data; second, the remaining parameters are estimated using the whole data and the previous estimates. The comparison between the algorithms was based on the [Formula: see text] goodness-of-fit measure: performance analysis was carried out on real data obtained by DW-MRI on 40 LARC patients.

RESULTS

The performance of the proposed algorithm was higher than that of LM in 64 % of cases; 'segmented' methods were poorer than our algorithm in 100 % of cases.

CONCLUSION

The proposed modified VARPRO algorithm can lead to better fit of the IVIM model to LARC DW-MRI data compared to other techniques.

A Simplified Model for Intravoxel Incoherent Motion Perfusion Imaging of the Brain

BACKGROUND AND PURPOSE

Despite a recent resurgence, intravoxel incoherent motion MRI faces practical challenges, including limited SNR and demanding acquisition and postprocessing requirements. A simplified approach using linear fitting of a subset of higher b-values has seen success in other organ systems. We sought to validate this method for evaluation of brain pathology by comparing perfusion measurements using simplified linear fitting to conventional biexponential fitting.

MATERIALS AND METHODS

Forty-nine patients with gliomas and 17 with acute strokes underwent 3T MRI, including DWI with 16 b-values (range, 0-900 s/mm²). Conventional intravoxel incoherent motion was performed using nonlinear fitting of the standard biexponential equation. Simplified intravoxel incoherent motion was performed using linear fitting of the log-normalized signal curves for subsets of b-values >200 s/mm². Comparisons between ROIs (tumors, strokes, contralateral brain) and between models (biexponential and simplified linear) were performed by using 2-way ANOVA. The root mean square error and coefficient of determination (R²) were computed for the simplified model, with biexponential fitting as the reference standard.

RESULTS

Perfusion maps using simplified linear fitting were qualitatively similar to conventional biexponential fitting. The perfusion fraction was elevated in high-grade (n = 33) compared to low-grade (n = 16) gliomas and was reduced in strokes compared to the contralateral brain (P < .001 for both main effects). Decreasing the number of b-values used for linear fitting resulted in reduced accuracy (higher root mean square error and lower R²) compared with full biexponential fitting.

CONCLUSIONS

Intravoxel incoherent motion perfusion imaging of common brain pathology can be performed by using simplified linear fitting, with preservation of clinically relevant perfusion information.

Effects of perfusion on DTI and DKI estimates in the skeletal muscle

PURPOSE

In this study, we evaluated the effects of perfusion of the skeletal muscle on diffusion tensor imaging (DTI) and diffusional kurtosis imaging (DKI) parameters and their reproducibility.

METHODS

Diffusion tensor imaging and DKI models, with and without intravoxel incoherent motion (IVIM) correction, were applied to simulated data at different physiological conditions and signal-to-noise ratio levels. Next, the same models were applied to data of the right calf of five healthy volunteers, acquired twice at 3 telsa. For six muscles, we evaluated the correlation of the perfusion signal fraction, with parameters derived from DTI and DKI, and performed repeatability analysis with and without IVIM correction. Additionally, the IVIM correction was compared to a multishell acquisition approach that minimizes perfusion effects on DTI estimates.

RESULTS

Simulations and acquired data showed that DTI and DKI estimates were biased proportionally to the perfusion signal fraction, and that IVIM correction was needed for accurate estimation of the DTI and DKI parameters. However, taking perfusion into account did not improve repeatability.

CONCLUSION

Blood perfusion has an effect on DTI and DKI estimations, but it can be minimized with IVIM correction or multishell acquisition strategies. Magn Reson Med 78:233-246, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging for Prediction of Early Arterial Blood Flow Stasis in Radioembolization of Breast Cancer Liver Metastases

PURPOSE

To retrospectively evaluate predictive value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for early arterial blood flow stasis during transarterial radioembolization (TARE) of liver dominant breast metastases (LdBM).

MATERIALS AND METHODS

Preinterventional 1.5T DWI (b0, b1, b2 = 0, 50, 800 s/mm(2)) data for 28 liver lobes of 18 female patients treated by resin-based radioembolization (10 bilobar and 8 unilobar treatments) were analyzed. Apparent diffusion coefficient (ADC) (0, 800) and an estimation of the true diffusion coefficient D' and of the perfusion fraction f' were calculated for the 2 largest metastases. Response rate at 3 months and survival were analyzed. Procedures without full dose application because of early stasis were assigned to group A (n = 15), and procedures with full dose application were assigned to group B (n = 13).

RESULTS

Metastases in group A showed significantly lower f' (0.035 ± 0.018 vs 0.076 ± 0.015, P < .0001) and a trend toward lower ADC(0, 800) with values given in 10(-6) mm(2)/s (1,066 ± 141 vs 1,189 ± 176, P = .051); no group difference was shown for D'. Groups were best discriminated by weighted mean f' values of the 2 largest metastases with accuracy of 100%. Mean tumor diameter before and after TARE was 51 mm ± 18 and 50 mm ± 24 in group A and 47 mm ± 27 and 48 mm ± 32 for group B. Imaging response did not differ between groups (P = .545). Overall survival did not differ significantly between group A (230 d) and B (155 d) (P = .124).

CONCLUSIONS

Perfusion-sensitive IVIM parameter f' may predict early blood flow stasis in patients undergoing TARE for LdBM. Determination of this parameter before intervention may increase awareness of the interventionalist and increase safety of microsphere administration.

The value of intravoxel incoherent motion model-based diffusion-weighted imaging for outcome prediction in resin-based radioembolization of breast cancer liver metastases

Purpose

To evaluate prognostic values of clinical and diffusion-weighted magnetic resonance imaging-derived intravoxel incoherent motion (IVIM) parameters in patients undergoing primary radioembolization for metastatic breast cancer liver metastases.

Subjects and methods

A total of 21 females (mean age 54 years, range 43–72 years) with liver-dominant metastatic breast cancer underwent standard liver magnetic resonance imaging (1.5 T, diffusion-weighted imaging with b-values of 0, 50, and 800 s/mm²) before and 4–6 weeks after radioembolization. The IVIM model-derived estimated diffusion coefficient D’ and the perfusion fraction f’ were evaluated by averaging the values of the two largest treated metastases in each patient. Kaplan–Meier and Cox regression analyses for overall survival (OS) were performed. Investigated parameters were changes in f’- and D’-values after therapy, age, sex, Eastern Cooperative Oncology Group (ECOG) status, grading of primary tumor, hepatic tumor burden, presence of extrahepatic disease, baseline bilirubin, previous bevacizumab therapy, early stasis during radioembolization, chemotherapy after radioembolization, repeated radioembolization and Response Evaluation Criteria in Solid Tumors (RECIST) response at 6-week follow-up.

Results

Median OS after radioembolization was 6 (range 1.5–54.9) months. In patients with therapy-induced decreasing or stable f’-values, median OS was significantly longer than in those with increased f’-values (7.6 [range 2.6–54.9] vs 2.6 [range 1.5–17.4] months, P<0.0001). Longer median OS was also seen in patients with increased D’-values (6 [range 1.6–54.9] vs 2.8 [range 1.5–17.4] months, P=0.008). Patients with remission or stable disease (responders) according to RECIST survived longer than nonresponders (7.2 [range 2.6–54.9] vs 2.6 [range 1.5–17.4] months, P<0.0001). An ECOG status ≤1 resulted in longer median OS than >1 (7.6 [range 2.6–54.9] vs 1.7 [range 1.5–4.5] months, P<0.0001). Pretreatment IVIM parameters and the other clinical characteristics were not associated with OS. Classification by f’-value changes and ECOG status remained as independent predictors of OS on multivariate analysis, while RECIST response and D’-value changes did not predict survival.

Conclusion

Following radioembolization of breast cancer liver metastases, early changes in the IVIM model-derived perfusion fraction f’ and baseline ECOG score were predictive of patient outcome, and may thus help to guide treatment strategy.

Intravoxel incoherent motion diffusion-weighted imaging of the pancreas: Characterization of benign and malignant pancreatic pathologies

PURPOSE

To evaluate the diagnostic value of apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) parameters in differentiating patients with either a normal pancreas (NP), pancreatic ductal adenocarcinoma (PDAC), neuroendocrine tumor (NET), solid pseudopapillary tumor (SPT), acute pancreatitis (AcP), vs. autoimmune pancreatitis (AIP).

MATERIALS AND METHODS

In all, 84 pathologically confirmed pancreatic tumors (60 PDACs, 15 NETs, 9 SPTs), 20 pancreatitis (13 AcPs, 7 AIPs), and 30 NP subjects underwent IVIM diffusion-weighted imaging using 10 b-values (0-900 sec/mm² ) at 1.5T. The ADC, pure molecular diffusion coefficient (D_slow ), perfusion fraction (f), and perfusion-related diffusion coefficient (D_fast ) were calculated and compared using a Kruskal-Wallis test and post-hoc Dunn procedure. Receiver operating characteristic (ROC) analysis was performed to assess diagnostic performance.

RESULTS

The f and D_fast of the PDAC were significantly lower than that of the NP (f = 0.10 vs. 0.24; D_fast  = 42.21 vs. 71.74 × 10^-3 mm² /sec; P < 0.05). In ROC analysis, f showed the best diagnostic performance (area-under-the-curve, 0.919) among all parameters in differentiating PDAC from NP (P ≤ 0.001). The f values of AcP (0.11) and AIP (0.13) and the D_fast values of SPT (20.48 × 10^-3 mm² /sec) and AcP (24.49 × 10^-3 mm² /sec) were significantly lower compared with NP (f = 0.24; D_fast  = 71.74 × 10^-3 mm² /sec; P < 0.05). For NET, the f (0.21) was significantly higher than that of PDAC (0.10, P < 0.01).

CONCLUSION

Perfusion-related parameters f and D_fast are more helpful in characterizing pancreatic diseases than ADC or D_slow . The PDCA, SPT, AcP, and AIP were characterized by reduced f and D_fast values compared with normal pancreas. The f value might help in differentiating between PDAC and NET.

LEVEL OF EVIDENCE

3 J. Magn. Reson. Imaging 2017;45:260-269.

Acute pancreatitis with gradient echo T2*-weighted magnetic resonance imaging

BACKGROUND

To study gradient recalled echo (GRE) T2*-weighted imaging (T2*WI) for normal pancreas and acute pancreatitis (AP).

METHODS

Fifty-one patients without any pancreatic disorders (control group) and 117 patients with AP were recruited. T2* values derived from T2*WI of the pancreas were measured for the two groups. The severity of AP was graded by the magnetic resonance severity index (MRSI) and the Acute Physiology and Chronic Healthy Evaluation II (APACHE II) scoring system. Logistic regression was used to analyze the relationship between the T2* values and AP severity. The usefulness of the T2* value for diagnosing AP and the relationship between the T2* values and the severity of AP were analyzed.

RESULTS

On GRE-T2*WI, the normal pancreas showed a well-marinated and consistently homogeneous isointensity. Edematous AP, as well as the non-necrotic area in necrotizing AP, showed ill-defined but homogeneous signal intensity. AP with pancreatic hemorrhage showed a decreased T2* value and a signal loss on the signal decay curve. The T2* value of pancreas in the AP group was higher than that of the control group (t=-8.20, P<0.05). The T2* value tended to increase along with the increase in MRSI scores but not with the APACHE II scores (P>0.05). AP was associated with a one standard deviation increment in the T2* value (OR =1.37; 95% CI: 1.216-1.532).

CONCLUSIONS

T2*WI demonstrates a few characteristics of the normal pancreas and AP, which could potentially be helpful for detecting hemorrhage, and contributes to diagnosing AP and its severity.

Clinical Intravoxel Incoherent Motion and Diffusion MR Imaging: Past, Present, and Future

The concept of diffusion magnetic resonance (MR) imaging emerged in the mid-1980s, together with the first images of water diffusion in the human brain, as a way to probe tissue structure at a microscopic scale, although the images were acquired at a millimetric scale. Since then, diffusion MR imaging has become a pillar of modern clinical imaging. Diffusion MR imaging has mainly been used to investigate neurologic disorders. A dramatic application of diffusion MR imaging has been acute brain ischemia, providing patients with the opportunity to receive suitable treatment at a stage when brain tissue might still be salvageable, thus avoiding terrible handicaps. On the other hand, it was found that water diffusion is anisotropic in white matter, because axon membranes limit molecular movement perpendicularly to the nerve fibers. This feature can be exploited to produce stunning maps of the orientation in space of the white matter tracts and brain connections in just a few minutes. Diffusion MR imaging is now also rapidly expanding in oncology, for the detection of malignant lesions and metastases, as well as monitoring. Water diffusion is usually largely decreased in malignant tissues, and body diffusion MR imaging, which does not require any tracer injection, is rapidly becoming a modality of choice to detect, characterize, or even stage malignant lesions, especially for breast or prostate cancer. After a brief summary of the key methodological concepts beyond diffusion MR imaging, this article will give a review of the clinical literature, mainly focusing on current outstanding issues, followed by some innovative proposals for future improvements.

Diffusion-weighted MR imaging of pancreatic cancer: A comparison of mono-exponential, bi-exponential and non-Gaussian kurtosis models

OBJECTIVES

To compare two Gaussian diffusion-weighted MRI (DWI) models including mono-exponential and bi-exponential, with the non-Gaussian kurtosis model in patients with pancreatic ductal adenocarcinoma.

MATERIALS AND METHODS

After written informed consent, 15 consecutive patients with pancreatic ductal adenocarcinoma underwent free-breathing DWI (1.5T, b-values: 0, 50, 150, 200, 300, 600 and 1000 s/mm²). Mean values of DWI-derived metrics ADC, D, D*, f, K and D_K were calculated from multiple regions of interest in all tumours and non-tumorous parenchyma and compared. Area under the curve was determined for all metrics.

RESULTS

Mean ADC and D_K showed significant differences between tumours and non-tumorous parenchyma (both P < 0.001). Area under the curve for ADC, D, D*, f, K, and D_K were 0.77, 0.52, 0.53, 0.62, 0.42, and 0.84, respectively.

CONCLUSION

ADC and D_K could differentiate tumours from non-tumorous parenchyma with the latter showing a higher diagnostic accuracy. Correction for kurtosis effects has the potential to increase the diagnostic accuracy of DWI in patients with pancreatic ductal adenocarcinoma.

Evaluation of a Simplified Intravoxel Incoherent Motion (IVIM) Analysis of Diffusion-Weighted Imaging for Prediction of Tumor Size Changes and Imaging Response in Breast Cancer Liver Metastases Undergoing Radioembolization: A Retrospective Single Center Analysis

To investigate the value of a simplified intravoxel incoherent motion (IVIM) analysis for evaluation of therapy-induced tumor changes and response of breast cancer liver metastases (mBRC) undergoing radioembolization.In 21 females (mean age 54 years, range 43-72) with mBRC tumor size changes and response evaluation criteria in solid tumors (RECIST) response to 26 primary radioembolization procedures were analyzed. Standard 1.5-T liver magnetic resonance imaging including respiratory-gated diffusion-weighted imaging (DWI) with b0 = 0 s/mm, b1 = 50 s/mm, b2 = 800 s/mm before and 6 weeks after each treatment was performed. In addition to the apparent diffusion coefficient (ADC)(0,800), the estimated diffusion coefficient D' and the perfusion fraction f' were determined using a simplified IVIM approach. For each radioembolization, the 2 largest treated metastases (if available) were analyzed. Lesions were categorized according to size changes into group A (reduction of longest diameter [LD]) and group B (LD increase) after 3 months. Radioembolization procedures were further categorized into "response" (partial response and stable disease) and "nonresponse" (progressive disease) according to RECIST after 3 months. ADC and D' are given in 10 mm/s.Forty-five metastases were analyzed. Thirty-two lesions were categorized as A; 13 as B. Before therapy, group A lesions showed significantly larger f'-values than B (P = 0.001), but ADC(0,800) and D' did not differ. After therapy, in group A lesions the ADC(0,800)- and D'-values increased and f' decreased (P < 0.0001); in contrast in group B lesions f' increased (P = 0.001). Groups could be differentiated by preinterventional f' and by changes of D' and f' between pre and postinterventional imaging (area under the curve [AUC] of 0.903, 0.747 and 1.0, respectively).Preinterventional parameters did not differ between responders and nonresponders according to RECIST. ADC(0,800)- and D'-values showed a larger increase in responders compared with nonresponders (P = 0.013 and P = 0.001, respectively). After therapy f'-values decreased significantly in responders (P = 0.001). Good to excellent prediction of long-term RECIST response was possible by therapy-induced changes in LD, D', and f' (AUC 0.903, 0.879, and 0.867, respectively).A simplified IVIM model-based analysis of early post-treatment DWI can deliver additional information on tumor size changes and long-term RECIST response after radioembolization of mBRC. The estimated perfusion fraction f' is better suited for response assessment than the conventional ADC(0,800) or D'. This can be useful to guide further treatment strategy.

Histogram Analysis of Apparent Diffusion Coefficient in Differentiating Pancreatic Adenocarcinoma and Neuroendocrine Tumor

The aim of this study was to investigate whether histogram analysis in diffusion-weighted (DW) magnetic resonance imaging (MRI) can help differentiate pancreatic adenocarcinomas from neuroendocrine tumors.Sixty-four patients with histologically confirmed 53 pancreatic adenocarcinomas or 19 neuroendocrine tumors underwent DW MRI. We evaluated the pixel distribution histogram parameters (mean, skewness, kurtosis, and entropy) of the apparent diffusion coefficient (ADC) values derived from b-values of 0 and 200 (ADC200), 0 and 400 (ADC400), or 0 and 800 (ADC800) s/mm(2). Histogram parameters were compared between pancreatic adenocarcinomas and neuroendocrine tumors, and the diagnostic performance was evaluated by using receiver operating characteristic (ROC) analysis.The mean ADC200 and ADC400 were significantly higher in neuroendocrine tumors than in pancreatic adenocarcinomas (P = 0.001 and P = 0.019, respectively). Pancreatic adenocarcinomas showed significantly higher skewness and kurtosis on ADC400 (P = 0.007 and P = 0.001, respectively) and ADC800 (P = 0.001 and P = 0.001, respectively). With all b-value combinations, the entropy of ADC values was significantly higher in pancreatic adenocarcinomas (P < 0.001 for ADC200; P = 0.001 for ADC400; P < 0.001 for ADC800), and showed the highest area under the ROC curve for diagnosing adenocarcinomas (0.77 for ADC200, 0.76 for ADC400, and 0.78 for ADC800).ADC histogram analysis of DW MRI can help differentiate pancreatic adenocarcinomas from neuroendocrine tumors.

Various diffusion magnetic resonance imaging techniques for pancreatic cancer

Pancreatic cancer is one of the most common malignant tumors and remains a treatment-refractory cancer with a poor prognosis. Currently, the diagnosis of pancreatic neoplasm depends mainly on imaging and which methods are conducive to detecting small lesions. Compared to the other techniques, magnetic resonance imaging (MRI) has irreplaceable advantages and can provide valuable information unattainable with other noninvasive or minimally invasive imaging techniques. Advances in MR hardware and pulse sequence design have particularly improved the quality and robustness of MRI of the pancreas. Diffusion MR imaging serves as one of the common functional MRI techniques and is the only technique that can be used to reflect the diffusion movement of water molecules in vivo. It is generally known that diffusion properties depend on the characterization of intrinsic features of tissue microdynamics and microstructure. With the improvement of the diffusion models, diffusion MR imaging techniques are increasingly varied, from the simplest and most commonly used technique to the more complex. In this review, the various diffusion MRI techniques for pancreatic cancer are discussed, including conventional diffusion weighted imaging (DWI), multi-b DWI based on intra-voxel incoherent motion theory, diffusion tensor imaging and diffusion kurtosis imaging. The principles, main parameters, advantages and limitations of these techniques, as well as future directions for pancreatic diffusion imaging are also discussed.

Comparison of the Diagnostic Performances of Three Techniques of ROI Placement for ADC Measurements in Pancreatic Adenocarcinoma

RATIONALE AND OBJECTIVES

To prospectively investigate and compare three techniques of region of interest (ROI) placement for apparent diffusion coefficient (ADC) measurements in patients with pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

Twenty-one patients with surgical pathology-proven PDAC and 18 healthy volunteers were included. Respiratory-triggered single-shot echo-planar diffusion-weighted imaging (b values = 0, 600 s/mm(2)) was used to calculate the ADC maps across all participants. Three readers independently measured the ADCs according to three ROI methods: whole-volume, single-slice, and small solid samples of tumor. Mean ADCs for the healthy pancreas were calculated using three measurements from pancreatic head to tail, and ADCs of distal pancreas to the tumor were also measured. The interobserver variability for the three techniques was measured using the interclass correlation coefficient. The diagnostic performances were calculated and compared using the receiver operating characteristic curves (ROC).

RESULTS

All the ADCs measured from the three ROI placements on PDAC were significantly lower than that from the normal pancreas. ADCs of solid tumor samples were significantly lower than that measured from whole volume or single slice (both P < .001). Only the ADCs measured from the solid sample ROI placements on tumor were observed significantly lower than the ADC of distal pancreatic parenchyma (P = .005). Areas under the ROC for the identification of PDAC, based on small solid samples, single-slice and whole-volume ROIs, respectively, were 0.939, 0.791, and 0.735.

CONCLUSIONS

ADC based on the small solid samples of tumor provided the highest diagnostic performance in assessing PDAC and was more accurate than ADCs measured from single-slice or whole-volume ROI.

Diffusion-weighted imaging of pancreatic cancer

Magnetic resonance imaging (MRI) is a reliable and accurate imaging method for the evaluation of patients with pancreatic ductal adenocarcinoma (PDAC). Diffusion-weighted imaging (DWI) is a relatively recent technological improvement that expanded MRI capabilities, having brought functional aspects into conventional morphologic MRI evaluation. DWI can depict the random diffusion of water molecules within tissues (the so-called Brownian motions). Modifications of water diffusion induced by different factors acting on the extracellular and intracellular spaces, as increased cell density, edema, fibrosis, or altered functionality of cell membranes, can be detected using this MR sequence. The intravoxel incoherent motion (IVIM) model is an advanced DWI technique that consent a separate quantitative evaluation of all the microscopic random motions that contribute to DWI, which are essentially represented by molecular diffusion and blood microcirculation (perfusion). Technological improvements have made possible the routine use of DWI during abdominal MRI study. Several authors have reported that the addition of DWI sequence can be of value for the evaluation of patients with PDAC, especially improving the staging; nevertheless, it is still unclear whether and how DWI could be helpful for identification, characterization, prognostic stratification and follow-up during treatment. The aim of this paper is to review up-to-date literature data regarding the applications of DWI and IVIM to PDACs.

Advances in diffusion-weighted imaging

Diffusion-weighted imaging (DWI) has become a routine component of clinical MR imaging. Its unique soft tissue contrast mechanism exploits differences in the motion of water molecules in vivo at a biologically meaningful scale. The clinical potential of DWI in lesion detection, characterization, and response assessment has been explored. This review briefly covers basic principles of DWI and introduces advances, specifically for abdominopelvic organs.

Apparent diffusion coefficient (ADC) measurements in pancreatic adenocarcinoma: A preliminary study of the effect of region of interest on ADC values and interobserver variability

PURPOSE

To assess the influence of region of interest (ROI) on tumor apparent diffusion coefficient (ADC) measurements and interobserver variability in pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

Twenty-two patients recruited with pathology-proven PDAC underwent diffusion-weighted imaging (DWI, 3.0T) prior to the surgical resection. Two independent readers measured tumor ADCs according to three ROI methods: whole-volume, single-slice, and small solid sample of tumor. Minimum and mean ADCs were obtained. The interobserver variability for each of the three methods was analyzed using interclass correlation coefficient (ICC) and Bland-Altman analysis. The minimum and mean ADCs among the ROI methods were compared using nonparametric tests.

RESULTS

The single-slice ROI method showed the best reproducibility in the minimum ADC measurements (mean difference ± limits of agreement between two readers were 0.025 ± 0.25 × 10(-3) mm2 /s; ICC, 0.92) among the three ROI methods. For the solid tumor sample ROI, both minimum ADC and mean ADC measurements reproducibility were the worst, with limits of agreement up to ±0.50 × 10(-3) mm2 /s and ±0.32 × 10(-3) mm2 /s, respectively (ICCs, 0.41/0.58). Both the minimum and mean ADCs demonstrated significant differences among the three ROI methods (both P < 0.001). The post-hoc analyses results showed no significant difference with regard to the mean ADCs between whole-volume and single-slice ROI methods (P = 0.14).

CONCLUSION

The ROI method had a considerable influence on both the minimum and mean ADC values and the interobserver variability in PDAC. The worst interobserver variability was observed for both the minimum and mean ADCs derived from small solid-sample ROI.

Whole-body diffusion kurtosis imaging: initial experience on non-Gaussian diffusion in various organs

INTRODUCTION

Diffusion kurtosis imaging (DKI) is based on a non-Gaussian diffusion model that should inherently better account for restricted water diffusion within the complex microstructure of most tissues than the conventional diffusion-weighted imaging (DWI), which presumes Gaussian distributed water molecule displacement probability. The aim of this investigation was to test the technical feasibility of in vivo whole-body DKI, probe for organ-specific differences, and compare whole-body DKI and DWI results.

MATERIALS AND METHODS

Eight healthy subjects underwent whole-body DWI on a clinical 3.0 T magnetic resonance imaging system. Echo-planar images in the axial orientation were acquired at b-values of 0, 150, 300, 500, and 800 mm²/s. Parametrical whole-body maps of the diffusion coefficient (D), the kurtosis (K), and the traditional apparent diffusion coefficient (ADC) were generated. Goodness of fit was compared between DKI and DWI fits using the sums of squared residuals. Data groups were tested for significant differences of the mean by paired Student t tests.

RESULTS

Good-quality parametrical whole-body maps of D, K, and ADC could be computed. Compared with ADC values, D values were significantly higher in the cerebral gray matter (by 30%) and white matter (27%), renal cortex (23%) and medulla (21%), spleen (101%), as well as erector spinae muscle (34%) (each P value <0.001). No significant differences between D and ADC were found in the cerebrospinal fluid (P = 0.08) and in the liver (P = 0.13). Curves of DKI fitted the measurement points significantly better than DWI curves did in most organs.

CONCLUSIONS

Whole-body DKI is technically feasible and may reflect tissue microstructure more meaningfully than whole-body DWI.

Microstructural characterization of normal and malignant human prostate tissue with vascular, extracellular, and restricted diffusion for cytometry in tumours magnetic resonance imaging

OBJECTIVE

The aim of this study was to demonstrate the feasibility of the recently introduced Vascular, Extracellular, and Restricted Diffusion for Cytometry in Tumours (VERDICT) framework for imaging prostate cancer with diffusion-weighted magnetic resonance imaging (DW-MRI) within a clinical setting.

MATERIALS AND METHODS

The VERDICT framework is a noninvasive microstructure imaging technique that combines an in-depth diffusion MRI acquisition with a mathematical model to estimate and map microstructural tissue parameters such as cell size and density and vascular perfusion. In total, 8 patients underwent 3-T MRI using 9 different b values (100-3000 s/mm). All patients were imaged before undergoing biopsy. Experiments with VERDICT analyzed DW-MRI data from patients with histologically confirmed prostate cancer in areas of cancerous and benign peripheral zone tissue. For comparison, we also fitted commonly used diffusion models such as the apparent diffusion coefficient (ADC), the intravoxel incoherent motion (IVIM), and the kurtosis model. We also investigated correlations of ADC and kurtosis with VERDICT parameters to gain some biophysical insight into the various parameter values.

RESULTS

Eight patients had prostate cancer in the peripheral zone, with Gleason score 3 + 3 (n = 1), 3 + 4 (n = 6), and 4 + 3 (n = 1). The VERDICT model identified a significant increase in the intracellular and vascular volume fraction estimates in cancerous compared with benign peripheral zone, as well as a significant decrease in the volume of the extracellular-extravascular space (EES) (P = 0.05). This is in agreement with manual segmentation of the biopsies for prostate tissue component analysis, which found proliferation of epithelium, loss of surrounding stroma, and an increase in vasculature. The standard ADC and kurtosis parameters were also significantly different (P = 0.05) between tissue types. There was no significant difference in any of the IVIM parameters (P = 0.11 to 0.29). The VERDICT parametric maps from voxel-by-voxel fitting clearly differentiated cancer from benign regions. Kurtosis and ADC parameters correlated most strongly with VERDICT's intracellular volume fraction but also moderately with the EES and vascular fractions.

CONCLUSIONS

The VERDICT model distinguished tumor from benign areas, while revealing differences in microstructure descriptors such as cellular, vascular, and EES fractions. The parameters of ADC and kurtosis models also discriminated between cancer and benign regions. However, VERDICT provides more specific information that disentangles the various microstructural features underlying the changes in ADC and kurtosis. These results highlight the clinical potential of the VERDICT framework and motivate the construction of a shorter, clinically viable imaging protocol to enable larger trials leading to widespread translation of the method.