Apparent diffusion coefficient-dependent voxelwise computed diffusion-weighted imaging: An approach for improving SNR and reducing T2 shine-through effects

Computed diffusion-weighted imaging with a low-apparent diffusion coefficient-pixel cut-off technique for breast cancer detection

OBJECTIVE

This study aimed to compare the image quality and diagnostic performance of computed diffusion-weighted imaging (DWI) with low-apparent diffusion coefficient (ADC)-pixel cut-off technique (cDWI cut-off) and actual measured DWI (mDWI).

METHODS

Eighty-seven consecutive patients with malignant breast lesions and 72 with negative breast lesions who underwent breast MRI were retrospectively evaluated. Computed DWI with high b-values of 800, 1200, and 1500 s/mm2 and ADC cut-off thresholds of none, 0, 0.3, and 0.6 (×10-3 mm2/s) were generated from DWI with two b-values (0 and 800 s/mm2). To identify the optimal conditions, two radiologists evaluated the fat suppression and lesion reduction failure using a cut-off technique. The contrast between breast cancer and glandular tissue was evaluated using region of interest analysis. Three other board-certified radiologists independently assessed the optimised cDWI cut-off and mDWI data sets. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis.

RESULTS

When an ADC cut-off threshold of 0.3 or 0.6 (× 10-3 mm2/s) was applied, fat suppression improved significantly (p < .05). The contrast of the cDWI cut-off with a b-value of 1200 or 1500 s/mm2 was better than the mDWI (p < .01). The ROC area under the curve for breast cancer detection was 0.837 for the mDWI and 0.909 for the cDWI cut-off (p < .01).

CONCLUSION

The cDWI cut-off provided better diagnostic performance than mDWI for breast cancer detection.

ADVANCES IN KNOWLEDGE

Using the low-ADC-pixel cut-off technique, computed DWI can improve diagnostic performance by increasing contrast and eliminating un-suppressed fat signals.

Computed high-b-value high-resolution DWI improves solid lesion detection in IPMN of the pancreas

OBJECTIVES

To examine the effect of high-b-value computed diffusion-weighted imaging (cDWI) on solid lesion detection and classification in pancreatic intraductal papillary mucinous neoplasm (IPMN), using endoscopic ultrasound (EUS) and histopathology as a standard of reference.

METHODS

Eighty-two patients with known or suspected IPMN were retrospectively enrolled. Computed high-b-value images at b = 1000 s/mm2 were calculated from standard (b = 0, 50, 300, and 600 s/mm2) DWI images for conventional full field-of-view (fFOV, 3 × 3 × 4 mm3 voxel size) DWI. A subset of 39 patients received additional high-resolution reduced-field-of-view (rFOV, 2.5 × 2.5 × 3 mm3 voxel size) DWI. In this cohort, rFOV cDWI was compared against fFOV cDWI additionally. Two experienced radiologists evaluated (Likert scale 1-4) image quality (overall image quality, lesion detection and delineation, fluid suppression within the lesion). In addition, quantitative image parameters (apparent signal-to-noise ratio (aSNR), apparent contrast-to-noise ratio (aCNR), contrast ratio (CR)) were assessed. Diagnostic confidence regarding the presence/absence of diffusion-restricted solid nodules was assessed in an additional reader study.

RESULTS

High-b-value cDWI at b = 1000 s/mm2 outperformed acquired DWI at b = 600 s/mm2 regarding lesion detection, fluid suppression, aCNR, CR, and lesion classification (p =  < .001-.002). Comparing cDWI from fFOV and rFOV revealed higher image quality in high-resolution rFOV-DWI compared to conventional fFOV-DWI (p ≤ .001-.018). High-b-value cDWI images were rated non-inferior to directly acquired high-b-value DWI images (p = .095-.655).

CONCLUSIONS

High-b-value cDWI may improve the detection and classification of solid lesions in IPMN. Combining high-resolution imaging and high-b-value cDWI may further increase diagnostic precision.

CLINICAL RELEVANCE STATEMENT

This study shows the potential of computed high-resolution high-sensitivity diffusion-weighted magnetic resonance imaging for solid lesion detection in pancreatic intraductal papillary mucinous neoplasia (IPMN). The technique may enable early cancer detection in patients under surveillance.

KEY POINTS

• Computed high-b-value diffusion-weighted imaging (cDWI) may improve the detection and classification of intraductal papillary mucinous neoplasms (IPMN) of the pancreas. • cDWI calculated from high-resolution imaging increases diagnostic precision compared to cDWI calculated from conventional-resolution imaging. • cDWI has the potential to strengthen the role of MRI for screening and surveillance of IPMN, particularly in view of the rising incidence of IPMNs combined with now more conservative therapeutic approaches.

A whole-body diffusion MRI normal atlas: development, evaluation and initial use

BACKGROUND

Statistical atlases can provide population-based descriptions of healthy volunteers and/or patients and can be used for region- and voxel-based analysis. This work aims to develop whole-body diffusion atlases of healthy volunteers scanned at 1.5T and 3T. Further aims include evaluating the atlases by establishing whole-body Apparent Diffusion Coefficient (ADC) values of healthy tissues and including healthy tissue deviations in an automated tumour segmentation task.

METHODS

Multi-station whole-body Diffusion Weighted Imaging (DWI) and water-fat Magnetic Resonance Imaging (MRI) of healthy volunteers (n = 45) were acquired at 1.5T (n = 38) and/or 3T (n = 29), with test-retest imaging for five subjects per scanner. Using deformable image registration, whole-body MRI data was registered and composed into normal atlases. Healthy tissue ADCmean was manually measured for ten tissues, with test-retest percentage Repeatability Coefficient (%RC), and effect of age, sex and scanner assessed. Voxel-wise whole-body analyses using the normal atlases were studied with ADC correlation analyses and an automated tumour segmentation task. For the latter, lymphoma patient MRI scans (n = 40) with and without information about healthy tissue deviations were entered into a 3D U-Net architecture.

RESULTS

Sex- and Body Mass Index (BMI)-stratified whole-body high b-value DWI and ADC normal atlases were created at 1.5T and 3T. %RC of healthy tissue ADCmean varied depending on tissue assessed (4-48% at 1.5T, 6-70% at 3T). Scanner differences in ADCmean were visualised in Bland-Altman analyses of dually scanned subjects. Sex differences were measurable for liver, muscle and bone at 1.5T, and muscle at 3T. Volume of Interest (VOI)-based multiple linear regression, and voxel-based correlations in normal atlas space, showed that age and ADC were negatively associated for liver and bone at 1.5T, and positively associated with brain tissue at 1.5T and 3T. Adding voxel-wise information about healthy tissue deviations in an automated tumour segmentation task gave numerical improvements in the segmentation metrics Dice score, sensitivity and precision.

CONCLUSIONS

Whole-body DWI and ADC normal atlases were created at 1.5T and 3T, and applied in whole-body voxel-wise analyses.

Diffusion Weighted Imaging of the Abdomen and Pelvis: Recent Technical Advances and Clinical Applications

Diffusion weighted imaging (DWI) serves as one of the most important functional magnetic resonance imaging techniques in abdominal and pelvic imaging. It is designed to reflect the diffusion of water molecules and is particularly sensitive to the malignancies. Yet, the limitations of image distortion and artifacts in single-shot DWI may hamper its widespread use in clinical practice. With recent technical advances in DWI, such as simultaneous multi-slice excitation, computed or reduced field-of-view techniques, as well as advanced shimming methods, it is possible to achieve shorter acquisition time, better image quality, and higher robustness in abdominopelvic DWI. This review discussed the recent advances of each DWI approach, and highlighted its future perspectives in abdominal and pelvic imaging, hoping to familiarize physicians and radiologists with the technical improvements in this field and provide future research directions.

Diagnostic Utility of Diffusion-Weighted Imaging and Apparent Diffusion Coefficient for Common Orbital Lesions: A Review

PURPOSE

To review and summarize the existing literature surrounding the clinical use of diffusion-weighted imaging and apparent diffusion coefficient (ADC) as diagnostic tools in differentiating common orbital lesions.

METHODS

A systematic literature review on the use of ADC and diffusion-weighted imaging sequences for orbital imaging was performed. Only original research articles that reported ADC values for benign or malignant lesions were included.

RESULTS

Malignant orbital tumors have an overall lower mean ADC value than benign masses. Orbital lymphoma is characterized by consistently lower ADC values compared with other malignant orbital masses; a threshold value less than 0.775 × 10 -3 mm 2 /s has been proposed to distinguish orbital lymphoma from other neoplastic and non-neoplastic orbital masses. To differentiate orbital inflammatory disease from lymphoma, an ADC threshold greater than 0.92 × 10 -3 mm 2 /s has been proposed.

CONCLUSIONS

Orbital masses encompass a host of benign and malignant etiologies and can present a diagnostic challenge on both clinical and radiological assessment. Recent advanced MRI techniques such as diffusion-weighted imaging and ADC can improve the diagnostic specificity for orbital disease, particularly in differentiating benign from malignant lesions and lymphoma from orbital inflammatory disease.

Bosniak classification of cystic renal masses, version 2019: Is it helpful to incorporate the diffusion weighted imaging characteristic of lesions into the guideline?

Objective

To improve understanding of diffusion weighted imaging (DWI) characteristic of MRI and clinical variables, further optimize the Bosniak classification for diagnosis of cystic renal masses (CRMs).

Methods

This study retrospectively analyzed 130 CRMs in 125 patients with CT or MRI, including 87 patients with DWI (b = 600, 1000 s/mm2). Clinical variables and histopathological results were recorded. Two radiologists in consensus analyzed images of each lesion for the size, thickness of wall, number of septum, enhancement of wall/septum, wall nodule, signal intensity on DWI, calcification, and cyst content. Clinical variables, CT and MRI image characteristics were compared with pathology or follow-up results to evaluate the diagnostic performance for CRMs.

Results

Of the 130 lesions in 125 patients, histological analysis reported that 36 were malignant, 38 were benign, and no change was found in 56 followed-up lesions (mean follow-up of 24 months). The incidences of cystic wall thickened, more septa, measurable enhancement of wall/septum, nodule(s) on CT/MRI, and high signal intensity on DWI were significantly higher in malignant than in benign CRMs (CT: p = 0.005, p < 0.001, p < 0.001, p < 0.001, p < 0.001; MRI: p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001, p < 0.001). Combination of MRI including DWI features with CT findings showed the highest area under ROC curve (0.973) in distinguishing benign and malignant CRMs.

Conclusions

Incorporating DWI characteristic of CRMs into Bosniak classification helps to improve diagnostic efficiency.

Diagnostic Accuracy of the Diffusion-Weighted Imaging Method Used in Association With the Apparent Diffusion Coefficient for Differentiating Between Primary Central Nervous System Lymphoma and High-Grade Glioma: Systematic Review and Meta-Analysis

Background

It is difficult to differentiate between a few primary central nervous system lymphoma (PCNSL) and high-grade glioma (HGG) using conventional magnetic resonance imaging techniques. The purpose of this study is to explore whether diffusion-weighted imaging (DWI) can be effectively used to differentiate between these two types of tumors by analyzing the apparent diffusion coefficient (ADC).

Research Design and Methods

Data presented in Pubmed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang Database, and China Science and Technology Journal Database (CQVIP) were analyzed. High-quality literature was included, and the quality was evaluated using the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) tool, and the studies were based on the inclusion and exclusion rules. The pooled sensitivity, pooled specificity, pooled positive likelihood ratio (PLR), pooled negative likelihood ratio (NLR), pooled diagnostic odds ratio (DOR), area under the curve (AUC) of the summary operating characteristic curve (SROC), and corresponding 95% confidence interval (CI) were calculated using the bivariate mixed effect model. Meta-regression analysis and subgroup analysis were used to explore the sources of heterogeneity. The publication bias was evaluated by conducting Deek's test.

Results

In total, eighteen high-quality studies were included. The pooled sensitivity was 0.82 (95% CI: 0.75–0.88), the pooled specificity was 0.87 (95% CI: 0.84–0.90), the pooled positive likelihood ratio was 6.49 (95% CI: 5.06–8.32), the pooled NLR was 0.21 (95% CI: 0.14–0.30), the pooled DOR was 31.31 (95% CI: 18.55–52.86), and the pooled AUC was 0.90 (95% CI: 0.87–0.92). Sample size, language and country of publication, magnetic field strength, region of interest (ROI), and cut-off values of different types of ADC can potentially be the sources of heterogeneity. There was no publication bias in this meta-analysis.

Conclusions

The results obtained from the meta-analysis suggest that DWI is characterized by high diagnostic accuracy and thus can be effectively used for differentiating between PCNSL and HGG.

Comparison of Computed and Acquired DWI in the Assessment of Rectal Cancer: Image Quality and Preoperative Staging

Objective

The aim of the study was to evaluate the computed diffusion-weighted images (DWI) in image quality and diagnostic performance of rectal cancer by comparing with the acquired DWI.

Methods

A total of 103 consecutive patients with primary rectal cancer were enrolled in this study. All patients underwent two DWI sequences, namely, conventional acquisition with b = 0 and 1,000 s/mm2 (aDWIb1,000) and another with b = 0 and 700 s/mm2 on a 3.0T MR scanner (MAGNETOM Prisma; Siemens Healthcare, Germany). The images (b = 0 and 700 s/mm2) were used to compute the diffusion images with b value of 1,000 s/mm2 (cDWIb1,000). Qualitative and quantitative analysis of both computed and acquired DWI images was performed, namely, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and signal intensity ratio (SIR), and also diagnostic staging performance. Interclass correlation coefficients, weighted κ coefficient, Friedman test, Wilcoxon paired test, and McNemar or Fisher test were used for repeatability and comparison assessment.

Results

Compared with the aDWIb1,000 images, the cDWIb1,000 ones exhibited significant higher scores of subjective image quality (all P &lt;0.050). SNR, SIR, and CNR of the cDWIb1,000 images were superior to those of the aDWIb1,000 ones (P &lt;0.001). The overall diagnostic accuracy of computed images was higher than that of the aDWIb1,000 images in T stage (P &lt;0.001), with markedly better sensitivity and specificity in distinguishing T1–2 tumors from the T3–4 ones (P &lt;0.050).

Conclusion

cDWIb1,000 images from lower b values might be a useful alternative option and comparable to the acquired DWI, providing better image quality and diagnostic performance in preoperative rectal cancer staging.

High-Resolution, High b-Value Computed Diffusion-Weighted Imaging Improves Detection of Pancreatic Ductal Adenocarcinoma

Background: Our purpose was to investigate the potential of high-resolution, high b-value computed DWI (cDWI) in pancreatic ductal adenocarcinoma (PDAC) detection. Materials and Methods: We retrospectively enrolled 44 patients with confirmed PDAC. Respiratory-triggered, diffusion-weighted, single-shot echo-planar imaging (ss-EPI) with both conventional (i.e., full field-of-view, 3 × 3 × 4 mm voxel size, b = 0, 50, 300, 600 s/mm2) and high-resolution (i.e., reduced field-of-view, 2.5 × 2.5 × 3 mm voxel size, b = 0, 50, 300, 600, 1000 s/mm2) imaging was performed for suspected PDAC. cDWI datasets at b = 1000 s/mm2 were generated for the conventional and high-resolution datasets. Three radiologists were asked to subjectively rate (on a Likert scale of 1–4) the following metrics: image quality, lesion detection and delineation, and lesion-to-pancreas intensity relation. Furthermore, the following quantitative image parameters were assessed: apparent signal-to-noise ratio (aSNR), contrast-to-noise ratio (aCNR), and lesion-to-pancreas contrast ratio (CR). Results: High-resolution, high b-value computed DWI (r-cDWI1000) enabled significant improvement in lesion detection and a higher incidence of a high lesion-to-pancreas intensity relation (type 1, clear hyperintense) compared to conventional high b-value computed and high-resolution high b-value acquired DWI (f-cDWI1000 and r-aDWI1000, respectively). Image quality was rated inferior in the r-cDWI1000 datasets compared to r-aDWI1000. Furthermore, the aCNR and CR were higher in the r-cDWI1000 datasets than in f-cDWI1000 and r-aDWI1000. Conclusion: High-resolution, high b-value computed DWI provides significantly better visualization of PDAC compared to the conventional high b-value computed and high-resolution high b-value images acquired by DWI.

Apparent diffusion coefficient (ADC): A potential in vivo biological surrogate of the incidentally discovered bone lesions at 3T MRI

PURPOSE

To probe the potential of apparent diffusion coefficient (ADC) to rectify the incidentally detected bone lesion on MRI into benign or malignant lesions.

MATERIALS AND METHODS

We retrospectively recruited 44 patients (24 males and 20 females); with 52 bone lesions, who underwent diffusion weighted (DW) imaging using multiple b-values on 3 T MRI. ADC maps were derived and analyzed by two radiologists; blinded to the final diagnosis. The mean ADC values were used for statistical analyses. The diagnosis was deduced by histopathological confirmation; in 32 lesions and strict clinical and imaging follow-up for at least 12 months; in 20 lesions.

RESULTS

The mean ADC value (mean±SD) of all malignant tumors (including cartilaginous neoplasms) was [0.92 ± 0.40] × 10-3 mm2/s. This significantly differed from those of both primary benign tumors [1.14 ± 0.24] × 10-3 mm2/s, (p = 0.011), and all non-malignant lesions collectively [1.29 ± 0.44] × 10-3 mm2/s, (p < 0.001). Using mADC value of ≤ 1.1 × 10-3 mm2/s resulted in 86.1% sensitivity and 62.5% specificity for characterizing a lesion as a malignant. The inter-rater reliability was almost perfect (95% CI = 0.954-0.985).

CONCLUSION

ADC could be a non-invasive in-vivo surrogate that may be able to discern the incidentally discovered osseous lesions into benign and malignant pathologies and guide further diagnostic workup.

Application Value of Mathematical Models of Diffusion-Weighted Magnetic Resonance Imaging in Differentiating Breast Cancer Lesions

Objective

To determine the application value of the mono-exponential model, dual-exponential model, and stretched-exponential model of MRI with diffusion-weighted imaging (DWI) in breast cancer (BC) lesions.

Methods

Totally 64 cases with BC admitted to our hospital between June 2019 and October 2020 were enrolled in this study. They had 71 lesions in total, including 40 benign tumor lesions (including 9 breast cyst lesions) and 31 malignant tumor lesions. After DWI examination, with normal glands as control, mono-exponential model (ADC) map, dual-exponential model (Standard-ADC) map, slow apparent diffusion coefficient (Slow-ADC) map, fast-apparent diffusion coefficient (Fast-ADC) map, and stretched-exponential model (DDC) map were processed, and corresponding values were generated. Then, the situation and significance of each parameter in breast cysts, benign breast tumor lesions, and malignant tumor lesions were analyzed.

Results

The values of ADC, Standard-ADC, and DDC of breast cysts were higher than those of normal glands (all P < 0.05), and the values of ADC and DDC of benign breast tumor lesions were lower than those of normal glands (P < 0.05). In addition, malignant breast tumor lesions had lower values of ADC, Standard-ADC, Slow-ADC, and DDC and a higher Fast-ADC value compared to normal glands (all P < 0.05). Compared with benign tumor lesions, malignant tumor lesions had lower values of ADC, Standard-ADC, Slow-ADC, and DDC and a higher value of Fast-ADC (all P < 0.05). Moreover, the receiver operating characteristic (ROC) curve-based analysis revealed that all the above models could be adopted to effectively evaluate the deterioration of benign breast tumor lesions (all P < 0.05), and DDC value had the most significant diagnostic effect on malignant tumor lesions (P < 0.05).

Conclusion

Both dual-exponential model and stretched-exponential model of DWI can help effectively evaluate the progression of benign breast tumors, and the stretched-exponential model is more effective in the diagnosis of malignant breast tumors. These models are of great help to the future clinical diagnosis of BC.

Intravoxel incoherent motion diffusion-weighted imaging in the characterization of Alzheimer's disease

OBJECTIVES

Alzheimer's disease (AD) is the most common type of dementia, and characterizing brain changes in AD is important for clinical diagnosis and prognosis. This study was designed to evaluate the classification performance of intravoxel incoherent motion (IVIM) diffusion-weighted imaging in differentiating between AD patients and normal control (NC) subjects and to explore its potential effectiveness as a neuroimaging biomarker.

METHODS

Thirty-one patients with probable AD and twenty NC subjects were included in the prospective study. IVIM data were subjected to postprocessing, and parameters including the apparent diffusion coefficient (ADC), slow diffusion coefficient (D_s), fast diffusion coefficient (D_f), perfusion fraction (fp) and D_f*fp were calculated. The classification model was developed and confirmed with cross-validation (group A/B) using Support Vector Machine (SVM). Correlations between IVIM parameters and Mini-Mental State Examination (MMSE) scores in AD patients were investigated using partial correlation analysis.

RESULTS

Diffusion MRI revealed significant region-specific differences that aided in differentiating AD patients from controls. Among the analyzed regions and parameters, the D_f of the right precuneus (PreR) (ρ = 0.515; P = 0.006) and the left cerebellum (CL) (ρ = 0.429; P = 0.026) demonstrated significant associations with the cognitive function of AD patients. An area under the receiver operating characteristics curve (AUC) of 0.84 (95% CI: 0.66, 0.99) was calculated for the validation in dataset B after the prediction model was trained on dataset A. When the datasets were reversed, an AUC of 0.90 (95% CI: 0.75, 1.00) was calculated for the validation in dataset A, after the prediction model trained in dataset B.

CONCLUSION

IVIM imaging is a promising method for the classification of AD and NC subjects, and IVIM parameters of precuneus and cerebellum might be effective biomarker for the diagnosis of AD.

Feasibility Study of Synthetic Diffusion-Weighted MRI in Patients with Breast Cancer in Comparison with Conventional Diffusion-Weighted MRI

OBJECTIVE

To investigate the clinical feasibility of synthetic diffusion-weighted imaging (sDWI) at different b-values in patients with breast cancer by assessing the diagnostic image quality and the quantitative measurements compared with conventional diffusion-weighted imaging (cDWI).

MATERIALS AND METHODS

Fifty patients with breast cancer were assessed using cDWI at b-values of 800 and 1500 s/mm² (cDWI₈₀₀ and cDWI₁₅₀₀) and sDWI at b-values of 1000 and 1500 s/mm² (sDWI₁₀₀₀ and sDWI₁₅₀₀). Qualitative analysis (normal glandular tissue suppression, overall image quality, and lesion conspicuity) was performed using a 4-point Likert-scale for all DWI sets and the cancer detection rate (CDR) was calculated. We also evaluated cancer-to-parenchyma contrast ratios for each DWI set in 45 patients with the lesion identified on any of the DWI sets. Statistical comparisons were performed using Friedman test, one-way analysis of variance, and Cochran's Q test.

RESULTS

All parameters of qualitative analysis, cancer-to-parenchyma contrast ratios, and CDR increased with increasing b-values, regardless of the type of imaging (synthetic or conventional) (p < 0.001). Additionally, sDWI₁₅₀₀ provided better lesion conspicuity than cDWI₁₅₀₀ (3.52 ± 0.92 vs. 3.39 ± 0.90, p < 0.05). Although cDWI₁₅₀₀ showed better normal glandular tissue suppression and overall image quality than sDWI₁₅₀₀ (3.66 ± 0.78 and 3.73 ± 0.62 vs. 3.32 ± 0.90 and 3.35 ± 0.81, respectively; p < 0.05), there was no significant difference in their CDR (90.0%). Cancer-to-parenchyma contrast ratios were greater in sDWI₁₅₀₀ than in cDWI₁₅₀₀ (0.63 ± 0.17 vs. 0.55 ± 0.18, p < 0.001).

CONCLUSION

sDWI₁₅₀₀ can be feasible for evaluating breast cancers in clinical practice. It provides higher tumor conspicuity, better cancer-to-parenchyma contrast ratio, and comparable CDR when compared with cDWI₁₅₀₀.

Comparative analysis of the diagnostic values of T2 mapping and diffusion-weighted imaging for sacroiliitis in ankylosing spondylitis

OBJECTIVE

To investigate the diagnostic values of T2 mapping and diffusion-weighted imaging (DWI) for active sacroiliitis in ankylosing spondylitis (AS) and to evaluate the correlations of T2 and ADC values with Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) and Spondyloarthritis Research Consortium of Canada (SPARCC) scores.

METHODS

A total of 77 AS patients with sacroiliitis and 45 healthy controls were enrolled. All patients were scanned by standard magnetic resonance imaging longitudinal relaxation time (T1)-weighted imaging (T1WI), fat-saturated T2-weighted imaging (FS-T2WI)] and DWI, and T2 mapping of the sacroiliac joints. According to whether subchondral bone marrow edema was present in the FS-T2WI sequence, the 77 patients were divided into an active group (41 cases) and an inactive group (36 cases). The T2 and apparent diffusion coefficient (ADC) values of the subchondral bone marrow were measured in the active group, the inactive group, and the healthy control group. The average T2 and ADC values were compared among the three groups. Receiver operating characteristic (ROC) curves were used to analyze the diagnostic efficacy of T2 and ADC values for sacroiliitis. The correlations of T2 and ADC values with the BASDAI score and the SPARCC score were analyzed.

RESULTS

The T2 and ADC values in the active group were higher than those in the inactive group, while that in the inactive group were significantly higher than those in the healthy control group (p < 0.0001). The T2 and ADC values of the AS patients were positively correlated with BASDAI scores, and the correlation coefficients (r) were 0.786 (p < 0.0001) and 0.842 (p < 0.0001), respectively. The areas under the ROC curves (AUCs) of T2 and ADC values between the active and inactive groups, the active group and the healthy control group, and the inactive group and the healthy control group were 0.889 (95% CI, 0.80-0.95) and 0.917 (95% CI, 0.83-0.97), 0.982 (95% CI, 0.93-1.00) and 0.984 (95% CI, 0.93-1.00), and 0.628 (95% CI, 0.51-0.73) and 0.871 (95% CI, 0.78-0.94), respectively. The T2 and ADC values of the AS patients in the active group were positively correlated with SPARCC scores, and the correlation coefficients (r) were 0.757 (p < 0.0001) and 0.764 (p < 0.0001), respectively.

CONCLUSION

T2 and ADC values can be used to quantitatively assess the activity of AS, and the efficacy of the ADC value in the diagnosis of AS was higher than that of the T2 value.

Diagnostic value of diffusion-weighted imaging with synthetic b-values in breast tumors: comparison with dynamic contrast-enhanced and multiparametric MRI

Objectives

To assess DWI for tumor visibility and breast cancer detection by the addition of different synthetic b-values.

Methods

Eighty-four consecutive women who underwent a breast-multiparametric-MRI (mpMRI) with enhancing lesions on DCE-MRI (BI-RADS 2–5) were included in this IRB-approved retrospective study from September 2018 to March 2019. Three readers evaluated DW acquired b-800 and synthetic b-1000, b-1200, b-1500, and b-1800 s/mm² images for lesion visibility and preferred b-value based on lesion conspicuity. Image quality (1–3 scores) and breast composition (BI-RADS) were also recorded. Diagnostic parameters for DWI were determined using a 1–5 malignancy score based on qualitative imaging parameters (acquired + preferred synthetic b-values) and ADC values. BI-RADS classification was used for DCE-MRI and quantitative ADC values + BI-RADS were used for mpMRI.

Results

Sixty-four malignant (average = 23 mm) and 39 benign (average = 8 mm) lesions were found in 80 women. Although b-800 achieved the best image quality score, synthetic b-values 1200–1500 s/mm² were preferred for lesion conspicuity, especially in dense breast. b-800 and synthetic b-1000/b-1200 s/mm² values allowed the visualization of 84–90% of cancers visible with DCE-MRI performing better than b-1500/b-1800 s/mm². DWI was more specific (86.3% vs 65.7%, p < 0.001) but less sensitive (62.8% vs 90%, p < 0.001) and accurate (71% vs 80.7%, p = 0.003) than DCE-MRI for breast cancer detection, where mpMRI was the most accurate modality accounting for less false positive cases.

Conclusion

The addition of synthetic b-values enhances tumor conspicuity and could potentially improve tumor visualization particularly in dense breast. However, its supportive role for DWI breast cancer detection is still not definite.

Key Points

• The addition of synthetic b-values (1200–1500 s/mm²) to acquired DWI afforded a better lesion conspicuity without increasing acquisition time and was particularly useful in dense breasts.

• Despite the use of synthetic b-values, DWI was less sensitive and accurate than DCE-MRI for breast cancer detection.

• A multiparametric MRI modality still remains the best approach having the highest accuracy for breast cancer detection and thus reducing the number of unnecessary biopsies.

Electronic supplementary material

The online version of this article (10.1007/s00330-020-07094-z) contains supplementary material, which is available to authorized users.

Noise-Corrected, Exponentially Weighted, Diffusion-Weighted MRI (niceDWI) Improves Image Signal Uniformity in Whole-Body Imaging of Metastatic Prostate Cancer

Purpose: To characterize the voxel-wise uncertainties of Apparent Diffusion Coefficient (ADC) estimation from whole-body diffusion-weighted imaging (WBDWI). This enables the calculation of a new parametric map based on estimates of ADC and ADC uncertainty to improve WBDWI imaging standardization and interpretation: NoIse-Corrected Exponentially-weighted diffusion-weighted MRI (niceDWI).

Methods: Three approaches to the joint modeling of voxel-wise ADC and ADC uncertainty (σ_ADC) are evaluated: (i) direct weighted least squares (DWLS), (ii) iterative linear-weighted least-squares (IWLS), and (iii) smoothed IWLS (SIWLS). The statistical properties of these approaches in terms of ADC/σ_ADC accuracy and precision is compared using Monte Carlo simulations. Our proposed post-processing methodology (niceDWI) is evaluated using an ice-water phantom, by comparing the contrast-to-noise ratio (CNR) with conventional exponentially-weighted DWI. We present the clinical feasibility of niceDWI in a pilot cohort of 16 patients with metastatic prostate cancer.

Results: The statistical properties of ADC and σ_ADC conformed closely to the theoretical predictions for DWLS, IWLS, and SIWLS fitting routines (a minor bias in parameter estimation is observed with DWLS). Ice-water phantom experiments demonstrated that a range of CNR could be generated using the niceDWI approach, and could improve CNR compared to conventional methods. We successfully implemented the niceDWI technique in our patient cohort, which visually improved the in-plane bias field compared with conventional WBDWI.

Conclusions: Measurement of the statistical uncertainty in ADC estimation provides a practical way to standardize WBDWI across different scanners, by providing quantitative image signals that improve its reliability. Our proposed method can overcome inter-scanner and intra-scanner WBDWI signal variations that can confound image interpretation.

Stimulated-echo diffusion-weighted imaging with moderate b values for the detection of prostate cancer

OBJECTIVES

Conventional spin-echo (SE) DWI leads to a fundamental trade-off depending on the b value: high b value provides better lesion contrast-to-noise ratio (CNR) by sacrificing signal-to-noise ratio (SNR), image quality, and quantitative reliability. A stimulated-echo (STE) DWI acquisition is evaluated for high-CNR imaging of prostate cancer while maintaining SNR and reliable apparent diffusion coefficient (ADC) mapping.

METHODS

In this prospective, IRB-approved study, 27 patients with suspected prostate cancer (PCa) were scanned with three DWI sequences (SE b = 800 s/mm², SE b = 1500 s/mm², and STE b = 800 s/mm²) after informed consent was obtained. ROIs were drawn on biopsy-confirmed cancer and non-cancerous tissue to perform quantitative SNR, CNR, and ADC measurements. Qualitative metrics (SNR, CNR, and overall image quality) were evaluated by three experienced radiologists. Metrics were compared pairwise between the three acquisitions using a t test (quantitative metrics) and Wilcoxon rank test (qualitative metrics).

RESULTS

Quantitative measurements showed that STE DWI at b = 800 s/mm² has significantly better SNR compared to SE DWI at b = 1500 s/mm² (p < 0.0001) and comparable CNR to high-b value SE DWI at b = 1500 s/mm² (p < 0.05) in the peripheral zone. Qualitative assessment showed preference to STE b = 800 s/mm² in SNR and SE b = 1500 s/mm² in CNR. The overall image quality and lesion detectability among most readers showed no significant preference between STE b = 800 s/mm² and SE b = 1500 s/mm². Further, STE DWI had similar ADC contrast between lesion and normal tissue as SE DWI at b = 800 s/mm² (p = 0.90).

CONCLUSION

STE DWI has the potential to provide high-SNR, high-CNR imaging of prostate cancer while also enabling reliable ADC mapping.

KEY POINTS

• Quantitative analysis showed that STE DWI at b = 800 s/mm²is able to achieve simultaneously high CNR, high SNR, and reliable ADC mapping, compared to SE b = 800 s/mm²and SE b = 1500 s/mm². • Qualitative assessment by three readers showed that STE DWI at b = 800 s/mm²has significantly higher SNR than SE b = 1500 s/mm². No preference between SE b = 1500 s/mm²and STE b = 800 s/mm²was determined in terms of CNR with no missed lesions were found in both acquisitions. • A single STE DWI acquisition at moderate b value (800-1000 s/mm²) may provide sufficient image quality and quantitative reliability for prostate cancer imaging within a shorter scan time, in place of two DWI acquisitions (one with moderate b value and one with high b value).

Effect of AQP4-RNAi in treating traumatic brain edema: Multi-modal MRI and histopathological changes of early stage edema in a rat model

Traumatic brain injury (TBI) is one of the leading causes of mortality and permanent disabilities worldwide. Brain edema following TBI remains to be the predominant cause of mortality and disability in patients worldwide. Previous studies have reported that brain edema is closely associated with aquaporin-4 (AQP4) expression. AQP4 is a water channel protein and mediates water homeostasis in a variety of brain disorders. In the current study, a rat TBI model was established, and the features of brain edema following TBI were assessed using multimodal MRI. The results of the multimodal MRI were useful, reliable and were used to evaluate the extent and the type of brain edema following TBI. Brain edema was also successfully alleviated using an intracerebral injection of AQP4 small interfering (si)RNA. The expression of AQP4 and its role in brain edema were also examined in the present study. The AQP4 siRNA was demonstrated to downregulate AQP4 expression following TBI and reduced brain edema at the early stages of TBI (6 and 12 h). The current study revealed the MRI features of brain edema and the changes in AQP4 expression exhibited following TBI, and the results provide important information that can be used to improve the early diagnosis and treatment of brain edema.

A primary analysis on measuring repeatability of the maximum diameter between CT and MR imaging for lung cancers

OBJECTIVE

To investigate the measurement reproducibility of the maximum diameter on MRI routine sequence (T1WI, T2WI, DWI) and CT in peripheral and central lung cancer, and to provide reference standard for evaluating treatment responses for lung cancer.

METHODS

53 patients with lung cancer underwent CT and 3.0T MR scanning. The maximum diameter was measured according to the RECIST1.1 standard on images of CT (lung and enhanced mediastinal window), MRI T2-BLADE, axial T1-VIBE and DWIb0, DWIb300, DWIb800, respectively. The reproducibility of the diameters was analyzed with intraclass correlation coefficient (ICC), and the distribution of measurement points with the Bland-Altman method. The difference analysis was assessed by paired samples t-test and nonparametric rank sum test, P < 0.05 is considered statistically significant.

RESULTS

Reproducibility of diameters derived from routine MRI and CT was good (ICC > 0.75). For peripheral lung cancer, there was no significant difference in diameters between CT and MRI. While for central lung cancer, there was significant difference in diameters measured between using CT and each MRI sequence. However, the diameters derived from T1-VIBE and T2-BLADE were not significantly different from all DWI sequences.

CONCLUSIONS

For peripheral lung cancer, the measurement on CT and routine MRI sequences can potentially replace each other after comprehensive consideration of examination purposes, but for central lung cancer, alternative use of CT and MRI in evaluating treatment responses for lung cancer should needs extra attention. The diameter measurement of lung cancer on DWI is consistent with that on T1WI and T2WI, suggesting that DWI can provide functional and morphological information.

Characterization of Alzheimer's Disease Using Ultra-high b-values Apparent Diffusion Coefficient and Diffusion Kurtosis Imaging

The aim of the study is to investigate the diffusion characteristics of Alzheimer’s disease (AD) patients using an ultra-high b-values apparent diffusion coefficient (ADC_uh) and diffusion kurtosis imaging (DKI). A total of 31 AD patients and 20 healthy controls (HC) who underwent both MRI examination and clinical assessment were included in this study. Diffusion weighted imaging (DWI) was acquired with 14 b-values in the range of 0 and 5000 s/mm². Diffusivity was analyzed in selected regions, including the amygdala (AMY), hippocampus (HIP), thalamus (THA), caudate (CAU), globus pallidus (GPA), lateral ventricles (LVe), white matter (WM) of the frontal lobe (FL), WM of the temporal lobe (TL), WM of the parietal lobe (PL) and centrum semiovale (CS). The mean, median, skewness and kurtosis of the conventional apparent diffusion coefficient (ADC), DKI (including two variables, D_app and K_app) and ADC_uh values were calculated for these selected regions. Compared to the HC group, the ADC values of AD group were significantly higher in the right HIP and right PL (WM), while the ADC_uh values of the AD group increased significantly in the WM of the bilateral TL and right CS. In the AD group, the K_app values in the bilateral LVe, bilateral PL/left TL (WM) and right CS were lower than those in the HC group, while the D_app value of the right PL (WM) increased. The ADC_uh value of the right TL was negatively correlated with MMSE (mean, r=-0.420, p=0.019). The ADC value and D_app value have the same regions correlated with MMSE. Compared with the ADC_uh, combining ADC_uh and ADC parameters will result in a higher AUC (0.894, 95%CI=0.803-0.984, p=0.022). Comparing to ADC or DKI, ADC_uh has no significant difference in the detectability of AD, but ADC_uh can better reflect characteristic alternation in unconventional brain regions of AD patients.

Improved Visualization of Middle Ear Cholesteatoma with Computed Diffusion-weighted Imaging

Computed DWI (cDWI) is a mathematical technique that calculates arbitrary higher b value images from at least two different lower b values. In addition, the removal of high intensity noise with image processing on cDWI could improve cholesteatoma-background contrast-to-noise ratio (CNR). In the present study, noise reduction was performed by the cut-off values of apparent diffusion coefficient (ADC) less than 0 and 0.4 × 10⁻³ s/mm². The cholesteatoma to non-cholesteatoma CNR was increased using a noise reduction algorithm for clinical setting.

Quantitative evaluation of computed and voxelwise computed diffusion-weighted imaging in breast cancer

OBJECTIVES

To assess the value of computed diffusion-weighted imaging (cDWI) and voxelwise computed diffusion-weighted imaging (vcDWI) in breast cancer.

METHODS

This retrospective study involved 130 patients (age range, 25-70 years; mean age ± standard deviation, 48.6 ± 10.5 years) with 130 malignant lesions, who underwent MRI examinations, including a DWI sequence, prior to needle biopsy or surgery. cDWIs with higher b-values of 1500, 2000, 2500, 3000, 3500, and 4000 s/mm², and vcDWI were generated from measured (m) DWI with two lower b-values of 0/600, 0/800, or 0/1000 s/mm². The signal-to-noise ratio (SNR) and contrast ratio (CR) of all image sets were computed and compared among different DWIs by two experienced radiologists independently. To better compare the CR with the SNR, the CR value was multiplied by 100 (CR100).

RESULTS

The CR of vcDWI, and cDWIs, except for cDWI₁₀₀₀, differed significantly from that of measured diffusion-weighted imaging (mDWI) (cDWI₁₀₀₀: CR = 0.4904, p = 0.394; cDWI₁₅₀₀: CR = 0.5503, p = 0.006; cDWI₂₀₀₀: CR = 0.5889, p < 0.001; cDWI₂₅₀₀: CR = 0.6109, p < 0.001; cDWI₃₀₀₀: mean = 0.6214, p < 0.001; cDWI₃₅₀₀: CR = 0.6245, p < 0.001; cDWI₄₀₀₀: CR = 0.6228, p < 0.001). The vcDWI provided the highest CR, while the CRs of all cDWI image sets improved with increased b-values. The SNR of neither cDWI₁₀₀₀ nor vcDWI differed significantly from that of mDWI, but the mean SNRs of the remaining cDWIs were significantly lower than that of mDWI. The SNRs of cDWIs declined with increasing b-values, and the initial decrease at low b-values was steeper than the gradual attenuation at higher b-values; the CR₁₀₀ rose gradually, and the two converged on the b-value interval of 1500-2000 s/mm² .

CONCLUSIONS

The highest CR was achieved with vcDWI; this could be a promising approach easier detection of breast cancer.

ADVANCES IN KNOWLEDGE

This study comprehensively compared and evaluated the value of the emerging post-processing DWI techniques (including a set of cDWIs and vcDWI) in breast cancer.

Feasibility and Diagnostic Performance of Voxelwise Computed Diffusion-Weighted Imaging in Breast Cancer

BACKGROUND

Conventional diffusion-weighted imaging (DWI) with high b-values may improve lesion conspicuity, but with a low signal intensity and thus a low signal-to-noise ratio (SNR). The voxelwise computed DWI (vcDWI) may generate high-quality images with a strong lesion signal and low background.

PURPOSE

To evaluate the feasibility and diagnostic performance of vcDWI.

STUDY TYPE

Retrospective.

POPULATION

In all, 67 patients with 72 lesions, 33 malignant and 39 benign.

FIELD STRENGTH/SEQUENCE

3T, including T₂ /T₁ , DWI with two b-values, and dynamic contrast-enhanced MRI (DCE-MRI).

ASSESSMENT

Computed DWI (cDWI) with high b-values of 1500, 2000, 2500 s/mm² (cDWI₁₅₀₀ , cDWI₂₀₀₀ , cDWI₂₅₀₀ ) and vcDWI were generated from measured DWI (mDWI). The mDWI, cDWIs and vcDWI were evaluated by three readers independently to determine lesion conspicuity, background signal suppression, overall image quality using 1-5 rating scales, as well as to give BI-RADS scores. The mean apparent diffusion coefficient (ADC) value for each lesion was measured.

STATISTICAL TESTS

Agreement among the three readers was evaluated by the intraclass correlation coefficient. Receiver operating characteristic (ROC) analysis was performed to compare the diagnostic performance based on reading of mDWI, cDWIs, vcDWI, and the measured ADC values.

RESULTS

vcDWI provided the best lesion conspicuity compared with mDWI and cDWIs (P < 0.005). For overall image quality, vcDWI was significantly better than cDWI (P < 0.005), but not significantly better compared with mDWI for two readers (P = 0.037 and P = 0.013) and significantly worse for the third reader (P < 0.005). Background signal suppression was the best on cDWI₂₅₀₀ , and better on vcDWI than on mDWI, cDWI₁₅₀₀ , and cDWI₂₀₀₀ . The AUC value for differential diagnosis was 0.868 for mDWI, 0.862 for cDWI₁₅₀₀ , 0.781 for cDWI₂₀₀₀ , 0.704 for cDWI₂₅₀₀ , 0.946 for vcDWI, 0.704 for ADC value, and 0.961 for DCE-MRI. DATA CONCLUSION: vcDWI was implemented without increasing scanning time, and it provided excellent lesion conspicuity for detection of breast lesions and assisted in differentiating malignant from benign breast lesions.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.

Voxelwise computed diffusion-weighted imaging for the detection of cytotoxic oedema in brain imaging: a pilot study

Aim To evaluate voxelwise computed diffusion-weighted imaging (vcDWI) for the detection of cytotoxic oedema in brain imaging and to quantify the benefit of lesion contrast in comparison to standard b = 1000 s/mm² by the example of acute ischaemic stroke. Materials and methods A retrospective evaluation of 66 patients (63 ± 15.9 years) suspected for acute ischaemic stroke who received diffusion-weighted magnetic resonance imaging and fluid-attenuated inversion recovery sequence. A neuroradiologist evaluated all examinations for acute ischaemic stroke based on diffusion-weighted imaging, the apparent diffusion coefficient and fluid-attenuated inversion recovery (reference standard) and 6 weeks later the vcDWI in a randomised manner. Time of analysis was noted. Signal intensities were acquired in lesions, in healthy tissue as well as in the cerebrospinal fluid. Contrast ratios and coefficients of variation were computed. Results A total of 218 lesions was found in 46/66 patients. vcDWI identified all patients and lesions correctly. The median evaluation time was 36 seconds (4-126 s) for the vcDWI and 44 seconds (9-186 s; P < 0.001) for the diffusion-weighted imaging/apparent diffusion coefficient reading. The contrast ratio in vcDWI (mean value 2.57, range 1.73-4.11) was higher than in b = 1000 s/mm² (2.33, 0.83-3.85, P = 0.03) and the apparent diffusion coefficient map (1.83, 1.00-3.00, P < 0.001), respectively. Coefficients of variation in lesions and tissue did not differ significantly between vcDWI and b = 1000 s/mm² ( P = 0.81/ P = 0.26). The signal intensity of cerebrospinal fluid was lower in vcDWI than in b = 1000 mm²/s (0.08 and 34.8, P < 0.001). Conclusion It could be shown that vcDWI has the potential to accelerate the detection of diffusion-restricted lesions in neuroimaging by improving the contrast ratios and reducing the T2 shine-through effect in comparison to standard diffusion-weighted imaging in brain imaging.

Computed Diffusion Weighted Imaging of the Liver Using Extrapolation Technique in Patients Who Underwent Liver Transplantation With Hepatocellular Carcinomas: Initial Experience and Feasibility Study

OBJECTIVE

This study aimed to evaluate the feasibility and image quality of computed diffusion weighted imaging (DWI) of the liver in patients with hepatocellular carcinoma (HCC).

METHODS

Twenty-four patients who underwent liver transplantation with HCC were enrolled. Computed DWI was synthesized for b-values of 800 (cDWI800) and 1200 s/mm (cDWI1200) using directly acquired DWI with b-values of 0, 50, and 500 s/mm. Signal intensity of HCC, background liver, and contrast-to-noise ratio were evaluated for directly acquired DWI of 800 s/mm (dDWI800), cDWI800, and cDWI1200. Two radiologists evaluated the image quality for contrast between HCC and liver, suppression of background signal and T2 shine-through, and overall image quality.

RESULTS

cDWI1200 showed the lowest contrast-to-noise ratio. Qualitative scores for background suppression and decreased T2 shine-through were highest for cDWI1200. However, contrast between HCC and background liver was worst in cDWI1200.

CONCLUSIONS

In computed DWI of high b-values, contrast between HCC and background liver was very low.

Computed diffusion weighted imaging (cDWI) and voxelwise-computed diffusion weighted imaging (vcDWI) for oncologic liver imaging: A pilot study

Objective

Aim of the study was to evaluate the influence of the selection of measured b-values on the precision of cDWI in the upper abdomen as well as on the lesion contrast of PET-positive liver metastases in cDWI and vcDWI.

Methods

We performed a retrospective analysis of 10 patients (4 m, 63.5 ± 12.9 y/o) with PET-positive liver metastases examined in 3 T-PET/MRI with b = 100,600,800,1000 and 1500s/mm². cDWI (cb1000/cb1500) and vcDWI were computed based on following combinations: i) b = 100/600 s/mm², ii) b = 100/800 s/mm², iii) b = 100/1000s/mm², iv) b = 100/600/1000s/mm² v) all measured b-values. Mean signal intensity (SI) and standard deviation (SD) in the liver, spleen, kidney, bone marrow and in liver lesions were acquired. The coefficient of variation (CV = SD/SI), the differences of SI between measured and calculated high b-value images and the lesion contrast (SI lesion/liver) were computed.

Results

With increasing upper measured b-values, the CV in cDWI and vcDWI decreased (CV in the liver in cb1500: 0.42 with b100/600 s/mm² and 0.28 with b100/b1000s/mm²) while the differences of measured and calculated b-value images decreased (in the liver in cb1500: 30.7% with b = 100/600 s/mm², 19.7% with b100/b1000s/mm²). In diffusion-restricted lesions, lesion contrast was at least 1.6 in cb1000 and 1.4 in cb1500, respectively, with an upper measured b-value of b = 800 s/mm² and 2.1 for vcDWI with an upper measured b-value of b = 1000s/mm². Overall, the lesion contrast was superior in cb1500 and vcDWI compared to cb1000 (15% and 11%, respectively).

Conclusion

Measuring higher upper b-values seems to lead to more precise computed high b-value images and a decrease of CV. vcDWI provides a comparable lesion contrast to b = 1500s/mm² and offers additionally the reduction of T2 shine-through effects. For vcDWI, measuring b = 1000s/mm² as upper b-value seems to be necessary to guarantee good lesion visibility in the liver based on our preliminary results.

Diffusion-weighted MR imaging of non-complicated hepatic cysts: Value of 3T computed diffusion-weighted imaging

Purpose

To investigate the utility of computed 3T diffusion-weighted imaging (c-DWI) for the diagnosis of non-complicated hepatic cysts with a focus on the T2 shine-through effect.

Materials and methods

In 50 patients with non-complicated hepatic cysts we acquired one set of DWIs (b-value 0 and 1000 s/mm²) at 1.5T, and two sets at 3T (b-value 0 and 1000 s/mm², TE 70 ms; b-value 0 and 600 s/mm², TE 60 ms). We defined the original DWIs acquired with b = 1000 s/mm² at 1.5T and 3T as “o-1.5T-1000” and “o-3T-1000”. c-DWIs were calculated with 3T DWI at b-values of 0 and 600 s/mm². c-DWI with b = 1000 and 1500 s/mm² were defined as “c-1000” and “c-1500”. Radiologists evaluated the signal intensity (SI) of the cysts using a 3-point score where 1 = not visible, 2 = discernible, and 3 = clearly visible. They calculated the contrast ratio (CR) between the cysts and the surrounding liver parenchyma on each DWIs and recorded the apparent diffusion coefficient (ADC) with a b-value = 0 and 1000 s/mm² on 1.5T- and 3T DWIs.

Results

Compared with o-1.5T-1000 DWI, the visual scores of all but the c-1500 DWIs were higher (p = 0.07 for c-1500- and p < 0.01 for the other DWIs). The CR at b = 1000 s/mm² was higher on o-3T-1000- than on o-1.5T-1000- (p < 0.01) but not higher than on c-1500 DWIs (p = 0.96). The CR at b = 0 s/mm² on 3T images with TE 70 ms was higher than on 1.5T images (p < 0.01). The ADC value was higher for 3T- than 1.5T images (p < 0.01).

Conclusions

Non-complicated hepatic cysts showed higher SI on o-3T-1000- than o-1.5T-1000 DWIs due to the T2-shine through effect. This high SI was suppressed on c-1500 DWIs.

Simple noise reduction for diffusion weighted images

Our purpose in this study was to reduce the noise in order to improve the SNR of Dw images with high b-value by using two correction schemes. This study was performed with use of phantoms made from water and sucrose at different concentrations, which were 10, 30, and 50 weight percent (wt%). In noise reduction for Dw imaging of the phantoms, we compared two correction schemes that are based on the Rician distribution and the Gaussian distribution. The highest error values for each concentration with use of the Rician distribution scheme were 7.3 % for 10 wt%, 2.4 % for 30 wt%, and 0.1 % for 50 wt%. The highest error values for each concentration with use of the Gaussian distribution scheme were 20.3 % for 10 wt%, 11.6 % for 30 wt%, and 3.4 % for 50 wt%. In Dw imaging, the noise reduction makes it possible to apply the correction scheme of Rician distribution.