Comparison of continuous-time random walk and fractional order calculus models in characterizing breast lesions using histogram analysis

OBJECTIVE

To compare the diagnostic performance of different mathematical models for DWI and explore whether parameters reflecting spatial and temporal heterogeneity can demonstrate better diagnostic accuracy than the diffusion coefficient parameter in distinguishing benign and malignant breast lesions, using whole-tumor histogram analysis.

METHODS

This retrospective study was approved by the institutional ethics committee and included 104 malignant and 42 benign cases. All patients underwent breast magnetic resonance imaging (MRI) with a 3.0 T MR scanner using the simultaneous multi-slice (SMS) readout-segment ed echo-planar imaging (rs-EPI). Histogram metrics of Mono- apparent diffusion coefficient (ADC), CTRW, and FROC-derived parameters were compared between benign and malignant breast lesions, and the diagnostic performance of each diffusion parameter was evaluated. Statistical analysis was performed using Mann-Whitney U test and receiver operating characteristic (ROC) curve.

RESULTS

The DFROC-median exhibited the highest AUC for distinguishing benign and malignant breast lesions (AUC = 0.965). The temporal heterogeneity parameter αCTRW-median generated a statistically higher AUC compared to the spatial heterogeneity parameter βCTRW-median (AUC = 0.850 and 0.741, respectively; p = 0.047). Finally, the combination of median values of CTRW parameters displayed a slightly higher AUC than that of FROC parameters, with no significant difference however (AUC = 0.971 and 0.965, respectively; p = 0.172).

CONCLUSIONS

The diffusion coefficient parameter exhibited superior diagnostic performance in distinguishing breast lesions when compared to the temporal and spatial heterogeneity parameters.

Comparison of conventional diffusion-weighted imaging, diffusion kurtosis imaging and intravoxel incoherent motion in characterization of sonographically indeterminate adnexal masses

PURPOSE

To evaluate the role of conventional diffusion weighted imaging, diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) in distinguishing benign from malignant adnexal masses.

METHODS

38 patients with 45 adnexal masses were enrolled in this prospective study and assessed with multiparametric MRI, including the IVIM-DKI sequence, on a 3 T MRI system. The mean apparent diffusion coefficient (ADC) from conventional DWI, the apparent diffusion coefficient derived from DKI (Dapp), the apparent kurtosis coefficient (Kapp), true diffusion coefficient (Dt), perfusion fraction (f) and pseudo-diffusion coefficient (Dp) were measured.

RESULTS

The mean ADC, Dapp, and Dt were significantly higher in benign adnexal masses than in malignant adnexal masses (p < 0.001). f and Dp were also significantly higher in benign adnexal masses, with p values of 0.026 and 0.002, respectively. Kapp was higher in malignant masses (p < 0.001). Among mean ADC, Dapp, and Dt, mean ADC had the highest area under the curve (AUC) of 0.885. However, no statistically significant differences were observed between the ROCs of various diffusion parameters.

CONCLUSION

The mean ADC, Dapp, and Kapp are useful parameters in discriminating between benign and malignant adnexal masses. Dt derived from IVIM also helps in distinguishing benign and malignant adnexal masses; however, no incremental role of IVIM and DKI over ADC could be identified in our study.

Relating pre-treatment non-Gaussian intravoxel incoherent motion diffusion-weighted imaging to human papillomavirus status and response in oropharyngeal carcinoma

Background and purpose

Diffusion-weighted imaging (DWI) is a promising technique for response assessment in head-and-neck cancer. Recently, we optimized Non-Gaussian Intravoxel Incoherent Motion Imaging (NG-IVIM), an extension of the conventional apparent diffusion coefficient (ADC) model, for the head and neck. In the current study, we describe the first application in a group of patients with human papillomavirus (HPV)-positive and HPV-negative oropharyngeal squamous cell carcinoma. The aim of this study was to relate ADC and NG-IVIM DWI parameters to HPV status and clinical treatment response.

Materials and methods

Thirty-six patients (18 HPV-positive, 18 HPV-negative) were prospectively included. Presence of progressive disease was scored within one year. The mean pre-treatment ADC and NG-IVIM parameters in the gross tumor volume were compared between HPV-positive and HPV-negative patients. In HPV-negative patients, ADC and NG-IVIM parameters were compared between patients with and without progressive disease.

Results

ADC, the NG-IVIM diffusion coefficient D, and perfusion fraction f were significantly higher, while pseudo-diffusion coefficient D* and kurtosis K were significantly lower in the HPV-negative compared to HPV-positive patients. In the HPV-negative group, a significantly lower D was found for patients with progressive disease compared to complete responders. No relation with ADC was observed.

Conclusion

The results of our single-center study suggest that ADC is related to HPV status, but not an independent response predictor. The NG-IVIM parameter D, however, was independently associated to response in the HPV-negative group. Noteworthy in the opposite direction as previously thought based on ADC.

Analysis of Diffusion-Weighted and T2-Weighted Imaging in the Prediction of Distinct Granulation Patterns of Somatotroph Adenomas

OBJECTIVE

The heterogeneity of the somatotroph adenomas, especially for sparsely granulated (SG) and densely granulated (DG) subtypes, has attracted great attention in identifying their imaging biomarker. The purpose of the current study was to compare the diagnostic performance of diffusion-weighted and T2-weighted magnetic resonance imaging (MRI) sequences for preoperatively distinguishing the granulation patterns of somatotroph adenomas.

METHODS

Thirty-two patients with a clinical diagnosis of somatotroph adenomas from October 2018 to March 2023 were included in this study. Coronal diffusion-weighted imaging (DWI) and T2-weighted MRI sequence data were collected from 3.0T MRI and compared between SG and DG groups. The immunohistochemistry was used to confirm the electron microscopy pathologic subtypes and Ki67 expression levels of somatotroph adenomas postoperatively.

RESULTS

Patients in the SG group had significantly higher signal intensity (SI) ratio of DWI (rDWI) (P < 0.001), lower SI ratio of apparent diffusion coefficient (rADC) (P < 0.001), and higher SI ratio of T2-weighted imaging (P = 0.011). The combined diagnosis index of rDWI and rADC had the highest diagnostic efficiency in predicting SG adenomas (sensitivity, 93.3%; specificity, 88.2%; P < 0.001). The rDWI and rADC values had positive and negative correlations with the Ki67 index and tumor maximum diameter, respectively. Lower rADC×103 was an independent predictor for SG adenomas.

CONCLUSIONS

Our results indicated that compared with previously used T2-weighted imaging, the DWI sequence, especially the combined diagnosis index of rDWI and rADC, could more efficiently distinguish the granulation patterns of somatotroph adenomas preoperatively.

Evaluations of the diagnostic performance of ZOOMit diffusion-weighted imaging and conventional diffusion-weighted imaging for breast lesions

Background

Diffusion-weighted imaging (DWI) is valuable in the screening, diagnosis, and grading of breast lesions. However, conventional DWI (C-DWI) is prone to chemical shift and distortion. ZOOMit DWI (Z-DWI), as an advanced magnetic resonance imaging (MRI) technique, applies two spatially selective parallel excitation pulses to focus sampling in the hope of obtaining more valuable information. This study aimed to evaluate and compare the image quality and feasibility of Z-DWI with those of C-DWI in breast lesions.

Methods

The study included 51 patients with breast lesions who underwent breast MRI from May 2021 to February 2022. All patients received Z-DWI and C-DWI sequences, with b values selected as 50 and 800 s/mm2 (Z-DWIb50, Z-DWIb800, C-DWIb50, and C-DWIb800). Apparent diffusion coefficient (ADC) values based on Z-DWI and C-DWI were calculated. For qualitative analysis, four image quality parameters were selected and assessed on a 4-point Likert scale (1 = poor and 4 = excellent). For quantitative analysis, ADC, relative ADC (rADC), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and tumor-to-parenchymal contrast (TPC) values were selected for comparison.

Results

Z-DWI had higher scores compared to C-DWI in terms of lesion conspicuity, anatomical details, distortion and artifacts, and overall image quality (P<0.05). Meanwhile, the agreement between the two readers was reasonably good [intraclass correlation coefficient (ICC) range, 0.360-0.881]. The SNR of Z-DWIb800 was better than that of C-DWIb800 (P<0.001). The Z-DWI ADC and rADC values of breast lesions were statistically significantly lower than those of C-DWI (mean ADC: P<0.001; rADC; P=0.005).

Conclusions

Z-DWI sequences were shown to have superior image quality. The ADC map of Z-DWI is more conducive to the imaging evaluation of breast lesions.

The influence of static portal pressure on liver biophysical properties

The liver is a highly vascularized organ where fluid properties, including vascular pressure, vessel integrity and fluid viscosity, play a critical role in gross mechanical properties. To study the effects of portal pressure, liver confinement, fluid viscosity, and tissue crosslinking on liver stiffness, water diffusion, and vessel size, we applied multiparametric magnetic resonance imaging (mpMRI), including multifrequency magnetic resonance elastography (MRE) and apparent diffusion coefficient (ADC) measurements, to ex vivo livers from healthy male rats (13.6±1.6 weeks) at room temperature. Four scenarios including altered liver confinement, tissue crosslinking, and vascular fluid viscosity were investigated with mpMRI at different portal pressure levels (0-17.5 cmH2O). Our experiments demonstrated that, with increasing portal pressure, rat livers showed higher water content, water diffusivity, and increased vessel sizes quantified by the vessel tissue volume fraction (VTVF). These effects were most pronounced in native, unconfined livers (VTVF: 300±120%, p<0.05, ADC: 88±29%, p<0.01), while still significant under confinement (confined: VTVF: 53±32%, p<0.01, ADC: 28±19%, p<0.05; confined-fixed: VTVF: 52±20%, p<0.001, ADC: 11±2%, p<0.01; confined-viscous: VTVF: 210±110%, p<0.01, ADC: 26±9%, p<0.001). Softening with elevated portal pressure (-12±5, p<0.05) occurred regardless of confinement and fixation. However, the liver stiffened when exposed to a more viscous inflow fluid (11±4%, p<0.001). Taken together, our results elucidate the complex relationship between macroscopic-biophysical parameters of liver tissue measured by mpMRI and vascular-fluid properties. Influenced by portal pressure, vascular permeability, and matrix crosslinking, liver stiffness is sensitive to intrinsic poroelastic properties, which, alongside vascular architecture and water diffusivity, may aid in the differential diagnosis of liver disease. STATEMENT OF SIGNIFICANCE: Using highly controllable ex vivo rat liver phantoms, hepatic biophysical properties such as tissue-vascular structure, stiffness, and water diffusivity were investigated using multiparametric MRI including multifrequency magnetic resonance elastography (MRE) and diffusion-weighted imaging (DWI). Through elaborate tuning of the experimental conditions such as the static portal pressure, flow viscosity, amount and distribution of fluid content in the liver, we identified the contributions of the fluid component to the overall imaging-based biophysical properties of the liver. Our finding demonstrated the sensitivity of liver stiffness to the hepatic poroelastic properties, which may aid in the differential diagnosis of liver diseases.

Quantitative apparent diffusion coefficient metrics for MRI-only suspicious breast lesions: any added clinical value?

Background

Suspicious breast lesions [Breast Imaging Reporting and Data System (BI-RADS) category 4 or 5] detected only by magnetic resonance imaging (MRI) and invisible on other initial imaging modalities (MRI-only lesions) are usually small and poorly characterized in previous literature, thus making diagnosis and management difficult. This study aimed to investigate the clinical significance of quantitative apparent diffusion coefficient (ADC) metrics derived from conventional diffusion-weighted imaging (DWI) on evaluating MRI-only lesions.

Methods

A total of 90 suspicious MRI-only lesions were evaluated, including 51 malignant and 39 benign lesions. Morphological and kinetic characteristics of all lesions (termed BI-RADS parameters) were described according to the BI-RADS lexicon on dynamic contrast-enhanced (DCE) imaging. Minimum, maximum, and mean ADC values (ADCmin, ADCmax, ADCmean) were obtained by measuring the ADC map of DWI. ADCheterogeneity was then obtained by the following formula: ADCheterogeneity = (ADCmax - ADCmin)/ADCmean. Diagnostic performance of these parameters was assessed and compared using the receiver operating characteristic (ROC) curve.

Results

Of the 90 MRI-only lesions, there were 45 masses and 45 non-mass lesions. Among BI-RADS parameters, only two different kinetic patterns were significantly different between benign and malignant groups (P=0.005 and P<0.001, respectively). The area under the ROC curve (AUC) of combined significant ADC parameters (ADCmin, ADCmean, and ADCmax, all P≤0.001) was significantly higher than that of the two different kinetic patterns (P=0.006 for both). For MRI-only masses, only ADCmean and ADCmax, among all BI-RADS and ADC parameters, had diagnostic value (combined AUC =0.833). For non-mass lesions, size, distribution, ADCmin, and ADCmean were significantly different between benign and malignant groups (P=0.004, P<0.001, P=0.001, and P<0.001, respectively). In addition, ADCmean had the highest diagnostic performance among all ADC parameters, regardless of mass or non-mass (AUC =0.825 and 0.812, respectively). ADCheterogeneity showed no significant differences, no matter in mass or non-mass groups (P=0.62 and 0.43, respectively).

Conclusions

In differentiating MRI-only suspicious lesions, quantitative ADC metrics generally performed better than BI-RADS parameters, and ADCmean is still the best ADC parameter to distinguish MRI-only lesions.

The Effectiveness of Volumetric MRI Histogram Analysis in Renal Cell Carcinoma

RATIONALE AND OBJECTIVES

This study investigated the utility of histogram parameters derived from diffusion-weighted imaging (DWI) for evaluating renal cell carcinoma (RCC) grading prior to surgery.

MATERIALS AND METHODS

This retrospective study included 88 patients who were histopathologically diagnosed with RCC and underwent magnetic resonance imaging (MRI) examinations. The patients were divided into two groups as well-differentiated (Group 1) and poorly differentiated (Group 2). Demographic data, preoperative MRI findings, MRI apparent diffusion coefficient (ADC) histogram analyzes, operation types, postoperative histopathological data and cancer stages of the patients were recorded. The histogram parameters of ADC values, comprising the mean, minimum, maximum, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles, as well as skewness, kurtosis, and variance, were calculated.

RESULTS

The study included 59 males and 29 women with an average age of 56.21 ± 1.33 years. There were 52 patients in Group 1 and 36 patients in Group 2. The ADCmin, ADCmean, ADCmax, 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of ADC values of the poorly differentiated group were all lower than those of the well-differentiated group. ADCmin and the 5th percentile of ADC values, as well as ADCmean and the 10th, 25th, 50th, and 75th percentiles of ADC values, showed a statistically significant difference (p < 0.05). The AUC, sensitivity, and specificity of the ADCmin value were 0.703, 56.3%, and 75.7%, respectively.

CONCLUSION

The present study indicated that histogram parameters generated from DWI were capable of differentiating between high-grade and low-grade RCC.

Impact of DWI and ADC values in Ovarian-Adnexal Reporting and Data System (O-RADS) MRI score

PURPOSE

Introduce DWI and quantitative ADC evaluation in O-RADS MRI system and observe how diagnostic performance changes. Assess its validity and reproducibility between readers with different experience in female pelvic imaging. Finally, evaluate any correlation between ADC value and histotype in malignant lesions.

MATERIALS AND METHODS

In total, 173 patients with 213 indeterminate adnexal masses (AMs) on ultrasound were subjected to MRI examination, from which 140 patients with 172 AMs were included in the final analysis. Standardised MRI sequences were used, including DWI and DCE sequences. Two readers, blinded to histopathological data, retrospectively classified AMs according to the O-RADS MRI scoring system. A quantitative analysis method was applied by placing a ROI on the ADC maps obtained from single-exponential DWI sequences. AMs considered benign (O-RADS MRI score 2) were excluded from the ADC analysis.

RESULTS

Excellent inter-reader agreement was found in the classification of lesions according to the O-RADS MRI score (K = 0.936; 95% CI). Two ROC curves were created to determine the optimal cut-off value for the ADC variable between O-RADS MRI categories 3-4 and 4-5, respectively, 1.411 × 10^-3 mm²/sec and 0.849 × 10^-3 mm²/sec. Based on these ADC values, 3/45 and 22/62 AMs were upgraded, respectively, to score 4 and 5, while 4/62 AMs were downgraded to score 3. ADC values correlated significantly with the ovarian carcinoma histotype (p value < 0.001).

CONCLUSION

Our study demonstrates the prognostic potential of DWI and ADC values in the O-RADS MRI classification for better radiological standardisation and characterisation of AMs.

Effects of fitting methods, high b-values and image quality on diffusion and perfusion quantification and reproducibility in the calf

PURPOSES

The study aimed to optimize diffusion-weighted imaging (DWI) image acquisition and analysis protocols in calf muscles by investigating the effects of different model-fitting methods, image quality, and use of high b-value and constraints on parameters of interest (POIs). The optimized modeling methods were used to select the optimal combinations of b-values, which will allow shorter acquisition time while achieving the same reliability as that obtained using 16 b-values.

METHODS

Test-retest baseline and high-quality DWI images of ten healthy volunteers were acquired on a 3T MR scanner, using 16 b-values, including a high b-value of 1200 s/mm², and structural T1-weighted images for calf muscle delineation. Three and six different fitting methods were used to derive ADC from monoexponential (ME) model and D_d, f_p, and D_p from intravoxel incoherent motion (IVIM) model, with or without the high b-value. The optimized ME and IVIM models were then used to determine the optimal combinations of b-values, obtainable with the least number of b-values, using the selection criteria of coefficient of variance (CV) ≤10% for all POIs.

RESULTS

The find minimum multivariate algorithm was more flexible and yielded smaller fitting errors. The 2-steps fitting method, with fixed D_d, performed the best for IVIM model. The inclusion of high b-value reduced outliers, while constraints improved 2-steps fitting only.

CONCLUSIONS

The optimal numbers of b-values for ME and IVIM models were nine and six b-values respectively. Test-retest reliability analyses showed that only ADC and D_d were reliable for calf diffusion evaluation, with CVs of 7.22% and 4.09%.

Value of quantitative apparent diffusion coefficients in differentiating low-grade gliomas from mixed neuronal-glial tumors

Purpose

To retrospectively assess if diffusion-weighted MR imaging (DWI) and quantitative apparent-diffusion coefficient (ADC) maps could be used to differentiate between low-grade gliomas (LGGs) and mixed neuronal-glial tumors (MNGTs including Dysembryoplastic Neuroepithelial Tumor and Ganglioglioma).

Materials and methods

We retrospectively searched the clinical, pathological, and radiological databases for a span of 9 years and identified 24 patients with biopsy proven LGG. This included WHO (fourth edition) grade I and II tumors including astrocytoma, oligoastrocytoma and oligodendrogliomas. We also identified 22 patients with MNGTs (WHO grade I) including 13 patients with DNET and 9 patients with Ganglioglioma. All patients with pathologically confirmed tumors who had MRI including DWI sequence were included in the study. Regions of interest (ROIs) of 0.1-0.15 cm² were manually positioned on the ADC maps and multiple values (10^-6 mm²/s) were obtained including the ADCmean. Optimal thresholds of ADC values and ADC ratios for distinguishing low-grade gliomas from mixed neuronal-glial tumors were determined by receiver operating characteristic (ROC) curve analysis.

Results

All the four ADC measurement variables, including the minimum (ADC min), the (ADC max) maximum, the mean of ADC values (ADC mean) and the ADC ratios (ADC mean/ADCnormal) showed significant difference between the MNGTs and LGGs. The most significant difference was seen with the maximum ADC value (ADC max) of the tumor where the values for LGGs were 1317 ± 314 whereas the values for MNGTs were 2134 ± 438. In both subsets of patients with MNGTs (DNET and Ganglioglioma), this difference was statistically significant (P = .015 and P = .0066, respectively). However, there was no significant difference between the ADC values of these subtypes of MNGTs.

Conclusion

The ADC values of MNGTs are significantly higher compared to LGGs and can be helpful in radiological demarcation of these two conditions. The high ADC of MNGTs may be attributable to the presence of large extracellular spaces and their cellularity, which is much lower than that of pure glial neoplasms.

Impact of obesity and diet on brain structure and function: a gut-brain-body crosstalk

Most societies witness an ever increasing prevalence of both obesity and dementia, a scenario related to often underestimated individual and public health burden. Overnutrition and weight gain have been linked with abnormal functionality of homoeostasis brain networks and changes in higher cognitive functions such as reward evaluation, executive functions and learning and memory. In parallel, evidence has accumulated that modifiable factors such as obesity and diet impact the gut-brain axis and modulate brain health and cognition through various pathways. Using neuroimaging data from epidemiological studies and randomised clinical trials, we aim to shed light on the underlying mechanisms and to determine both determinants and consequences of obesity and diet at the level of human brain structure and function. We analysed multimodal 3T MRI of about 2600 randomly selected adults (47 % female, 18-80 years of age, BMI 18-47 kg/m²) of the LIFE-Adult study, a deeply phenotyped population-based cohort. In addition, brain MRI data of controlled intervention studies on weight loss and healthy diets acquired in lean, overweight and obese participants may help to understand the role of the gut-brain axis in food craving and cognitive ageing. We find that higher BMI and visceral fat accumulation correlate with accelerated brain age, microstructure of the hypothalamus, lower thickness and connectivity in default mode- and reward-related areas, as well as with subtle grey matter atrophy and white matter lesion load in non-demented individuals. Mediation analyses indicated that higher visceral fat affects brain tissue through systemic low-grade inflammation, and that obesity-related regional changes translate into cognitive disadvantages. Considering longitudinal studies, some, but not all data indicate beneficial effects of weight loss and healthy diets such as plant-based nutrients and dietary patterns on brain ageing and cognition. Confounding effects of concurrent changes in other lifestyle factors or false positives might help to explain these findings. Therefore a more holistic intervention approach, along with open science tools such as data and code sharing, in-depth pre-registration and pooling of data could help to overcome these limitations. In addition, as higher BMI relates to increased head micro-movements during MRI, and as head motion in turn systematically induces image artefacts, future studies need to rigorously control for head motion during MRI to enable valid neuroimaging results. In sum, our results support the view that overweight and obesity are intertwined with markers of brain health in the general population, and that weight loss and plant-based diets may help to promote brain plasticity. Meta-analyses and longitudinal cohort studies are underway to further differentiate causation from correlation in obesity- and nutrition-brain research.

Fibroma-like PEComa: a newly recognized soft tissue neoplasm in tuberous sclerosis patients-imaging features and review of literature

Perivascular epithelioid cell tumors (PEComas) are rare mesenchymal neoplasms composed of spindled to epithelioid cells that co-express both melanocytic and myogenic markers. Recently, in 2018, a distinctive variant of PEComa has been described that arises in association with tuberous sclerosis complex (TSC) and resembles a fibroma by conventional morphology (called fibroma-like PEComa). Herein, we describe a case of a fibroma-like PEComa in a 4-year-old male child with a known diagnosis of tuberous sclerosis who presented with a firm mass along the anteromedial aspect of the right knee. The mass was excised, and microscopic examination showed bland spindled to stellate cells embedded in a dense collagenous stroma, morphologically resembling a fibroma. Immunohistochemistry analysis showed positivity for desmin (a myogenic marker) and HMB45 (a melanocytic marker), a hallmark for PEComas. To our knowledge, only six cases of fibroma-like PEComa have been described in the literature so far and this is the first report of such a tumor in the medial retinaculum of the knee joint with illustrations of conventional and diffusion imaging features. This case highlights the unique association of fibroma-like PEComa lesions with TSC. This should be considered a differential diagnosis for T2 hypointense masses in tuberous sclerosis patients. In addition, a diagnosis of fibroma-like PEComa should prompt further evaluation for associated TSC.

Value of diffusion-weighted imaging in preoperative evaluation and prediction of postoperative supplementary therapy for patients with cervical cancer

Background

With the continuous progress of medical imaging technology, evaluation of cervical cancer is increasingly dependent on imaging methods. Diffusion-weighted imaging (DWI) plays an important role, and apparent diffusion coefficient (ADC) value is a unique quantitative parameter in the research of cervical cancer.

Methods

In this prospective study, a total of 273 patients diagnosed with stage IB1 to IIIC1 cervical cancer based on the International Federation of Gynecology and Obstetrics (FIGO) 2018 staging guidelines who underwent pelvic 3.0T magnetic resonance imaging (MRI), including MRI and DWI, were enrolled, and the diagnostic value of preoperative staging of cervical cancer was compared between the MRI and DWI groups. The DWI group was used to explore the potential association of mean ADC (ADC_mean) with different pathological characteristics and receiver operating characteristic (ROC) curves of ADC_mean generated to predict the appropriate postoperative supplementary therapy.

Results

The diagnostic coincidence rate of DWI was higher than that of MRI in preoperative staging of cervical cancer (χ², P<0.05) and determined as stages IB1 + IB2 + IIA1 (90.91%), IB3 + IIA2 (93.48%), and IIIC1p (95.16%). The DWI staging results were consistent with postoperative pathological staging (Kappa value =0.865, P<0.001). We observed significant differences in ADC_mean values in relation to pathological type, histological grade, depth of stromal infiltration, tumor diameter, lymphovascular invasion, and pelvic lymph node metastasis of cervical cancer (all P<0.05). The area under the ROC curve (AUC) was 0.815, with the best predictive value for postoperative supplementary therapy in cervical cancer (sensitivity 80.0%, specificity 74.0%) at ADC_mean of 0.910×10^-3 mm²/s.

Conclusions

The DWI is a useful tool for preoperative evaluation of cervical cancer. In local cervical lesions, ADC_mean varies in relation to different clinicopathological characteristics and a reference index of <0.910×10^-3 mm²/s can be effectively applied to predict the need for postoperative supplementary therapy.

New and Advanced Magnetic Resonance Imaging Diagnostic Imaging Techniques in the Evaluation of Cranial Nerves and the Skull Base

The skull base and cranial nerves are technically challenging to evaluate using magnetic resonance (MR) imaging, owing to a combination of anatomic complexity and artifacts. However, improvements in hardware, software and sequence development seek to address these challenges. This section will discuss cranial nerve imaging, with particular attention to the techniques, applications and limitations of MR neurography, diffusion tensor imaging and tractography. Advanced MR imaging techniques for skull base pathology will also be discussed, including diffusion-weighted imaging, perfusion and permeability imaging, with a particular focus on practical applications.

The correlation between magnetic resonance diffusion parameters and Ki-67 and PCNA in hepatic fibrosis and cirrhosis rats

BACKGROUND

The aim of this study was to assess the value of different 1.5 T MRI apparent diffusion coefficient (ADC) and exponential apparent diffusion coefficient (EADC) values in diagnosing the stages of liver cirrhosis. Sprague-Dawley (SD) rats were randomly divided into the experimental group and the control group.

METHODS

The experimental group was injected with thioacetamide intraperitoneally 3 times per week. After routine MR scanning, diffusion-weighted imaging (DWI) was processed by spin echo-echo planar imaging (SE-EPI) to generate the ADC value and EADC image. The liver ADC and EADC values of rats were measured in the control and experimental groups, followed by Masson staining and hematoxylin and eosin staining. Furthermore, immunohistochemistry was performed to detect Ki-67 and PCNA expression in liver tissues.

RESULTS

In the control group, the differences in ADC and EADC values between the liver fibrosis and cirrhosis group were different. The ADC values of the liver fibrosis stage I-II, III-IV, and cirrhosis rats in the experimental group were lower than the control group, while the EADC values were higher than the control group. The ADC values of the liver fibrosis stage III-IV group and cirrhosis nodules group were lower than the control group. There were significant differences in EADC values between the cirrhotic nodule groups and the control group.

CONCLUSIONS

DWI-ADC values showed a negative correlation between SD rat liver fibrosis and cirrhosis pathology classification.

Breast Cancer Conspicuity on Computed Versus Acquired High b-Value Diffusion-Weighted MRI

RATIONALE AND OBJECTIVES

On unenhanced diffusion-weighted imaging (DWI), computing or synthesizing high b-value images from lower b-value acquisitions can enhance breast cancer visibility. This study aimed to evaluate relative lesion conspicuity on computed versus acquired diffusion-weighted images and investigate clinical characteristics influencing optimal b-values.

MATERIALS AND METHODS

Women with newly diagnosed breast cancer were prospectively enrolled and underwent 3T breast MRI with DWI. Lesion contrast-to-noise ratio (CNR) was measured across a range of b-values (0-2500 s/mm²) for computed and acquired DWI. Three readers independently compared lesion visibility between computed and acquired DWI and selected the optimal b-value. Computed versus acquired DWI was compared quantitatively based on CNR by paired t-test and qualitatively based on reader preference using a sign test. Optimal b-values by qualitative and quantitative assessment were compared by paired t-test, and associations with clinical characteristics were assessed by Wilcoxon rank sum test.

RESULTS

The study included 30 women (median age, 48 years); 28 with invasive carcinoma, 2 DCIS. Lesion CNR was higher on acquired versus computed images (p = 0.018), while lesion visibility by reader assessment was not different (p = 0.36). Optimal b-values selected by readers (mean, b = 1411 ± 383 s/mm²) were slightly higher than those based on peak CNR (b = 1233 ± 463 s/mm², p = 0.023), and were higher for younger (≤50 years) versus older women (p = 0.002) and dense versus nondense breasts (p = 0.015).

CONCLUSION

Lesion CNR on computed high b-value images was slightly reduced versus acquired images, but our study suggests that this did not significantly impact lesion visibility. Computing high b-value images offers extra flexibility to adjust b-value during interpretation.

Single-direction diffusion-weighted imaging may be a simple complementary sequence for evaluating fetal corpus callosum

OBJECTIVES

To explore the feasibility of single-direction diffusion-weighted imaging (DWI) for assessing the fetal corpus callosum (CC).

METHODS

This prospective study included 67 fetuses with normal CC and 35 fetuses suspected with agenesis of the corpus callosum (ACC). The MR protocols included HASTE, TrueFISP, and single-direction DWI. Two radiologists independently evaluated the optimal visibility and the contrast ratio (CR) of the normal fetal CC. The Chi-squared test or Fisher's exact test was used to compare the proportions of "good" visibility (score ≥ 3, and the CC was almost/entirely visible) between single-direction DWI and HASTE/TrueFISP. The CR difference between single-direction DWI and HASTE/TrueFISP was detected using the paired t-test. The diagnostic accuracies were determined by comparison with postnatal imaging. In fetuses suspected of ACC, we measured and compared the length and area of the mid-sagittal CC in the single-direction DWI images.

RESULTS

The proportion of "good" visibility in single-direction DWI was higher than that in HASTE/TrueFISP, with p < 0.0001. The mean CR from single-direction DWI was also higher than that of TrueFISP and HASTE (both with p < 0.0001). The diagnostic accuracy of the single-direction DWI combined with HASTE/TrueFisp (97.1%, 34/35) was higher than that of the Haste/TrueFISP (74.3%, 26/35) (p = 0.013). The length and area of the PACC (p < 0.001, p = 0.001, respectively) and HCC (p < 0.001, p = 0.018, respectively) groups were significantly lower than those of the normal group.

CONCLUSIONS

The single-direction DWI is feasible in displaying fetal CC and can be a complementary sequence in diagnosing ACC.

KEY POINTS

• We suggest a simple method for the display of the fetal CC. • The optimal visibility and contrast ratio from single-direction DWI were higher than those from HASTE and TrueFISP. • The diagnostic accuracy of the single-direction DWI combined with HASTE/TrueFISP sequences (97.1%, 34/35) was higher than that of the Haste/TrueFISP (74.3%, 26/35).

Value of Gd-EOB-DTPA-Enhanced MRI and Diffusion-Weighted Imaging in Detecting Residual Hepatocellular Carcinoma After Drug-Eluting Bead Transarterial Chemoembolization

RATIONALE AND OBJECTIVES

To investigate the value of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) in diagnosing residual hepatocellular carcinoma (HCC) after drug-eluting bead transarterial chemoembolization (DEB-TACE).

MATERIALS AND METHODS

Sixty-two patients (50 men, 12 women; mean age, 56.8 ± 1.4 years) with 74 HCCs who underwent Gd-EOB-DTPA-enhanced MRI and DWI in 1-2-month intervals after DEB-TACE were retrospectively studied. Imaging features derived from Gd-EOB-DTPA-enhanced MRI and DWI were analyzed and compared between residual HCCs and necrotic tumors. The sensitivity and specificity of Gd-EOB-DTPA-enhanced MRI and DWI with quantitative apparent diffusion coefficient (ADC) values in diagnosing residual HCCs were calculated and compared, based on the reference standard of pathology and/or angiography.

RESULTS

Thirty-three residual HCCs and 41 necrotic tumors were diagnosed. Residual HCCs presented characteristics of arterial hypervascularity (90.91%) and DWI hyperintensity (78.78%), which were of importance in differentiating necrotic tumors (p< 0.05). DWI showed lower sensitivity (78.79% vs. 96.97%, p< 0.001) and specificity (78.05% vs. 100%, p< 0.001) than Gd-EOB-DTPA-enhanced MRI in diagnosing residual HCCs after DEB-TACE. Residual HCCs had a significantly higher mean ADC value than necrotic tumors (1.30 ± 0.32 × 10^-3 mm²/s vs. 1.55 ± 0.50 × 10^-3 mm²/s, p< 0.001). Receiver operating characteristic curve analysis for identifying residual HCCs demonstrated that the threshold ADC value of 1.25 × 10^-3 mm²/s had 84.85% sensitivity and 87.80% specificity.

CONCLUSION

Gd-EOB-DTPA-enhanced MRI is superior to DWI in diagnosing residual HCCs after DEB-TACE, and arterial hypervascularity and DWI hyperintensity are important imaging features in distinguishing residual HCCs from necrotic tumors.

SYLVIUS: A multimodal and multidisciplinary platform for epilepsy surgery

BACKGROUND AND OBJECTIVE

We present SYLVIUS, a software platform intended to facilitate and improve the complex workflow required to diagnose and surgically treat drug-resistant epilepsies. In complex epilepsies, additional invasive information from exploration with stereoencephalography (SEEG) with deep electrodes may be needed, for which the input from different diagnostic methods and clinicians from several specialties is required to ensure diagnostic efficacy and surgical safety. We aim to provide a software platform with optimal data flow among the different stages of epilepsy surgery to provide smooth and integrated decision making.

METHODS

The SYLVIUS platform provides a clinical workflow designed to ensure seamless and safe patient data sharing across specialities. It integrates tools for stereo visualization, data registration, transfer of electrode plans referred to distinct datasets, automated postoperative contact segmentation, and novel DWI tractography analysis. Nineteen cases were retrospectively evaluated to track modifications from an initial plan to obtain a final surgical plan, using SYLVIUS.

RESULTS

The software was used to modify trajectories in all 19 consulted cases, which were then imported into the robotic system for the surgical intervention. When available, SYLVIUS provided extra multimodal information, which resulted in a greater number of trajectory modifications.

CONCLUSIONS

The architecture presented in this paper streamlines epilepsy surgery allowing clinicians to have a digital clinical tool that allows recording of the different stages of the procedure, in a common multimodal 2D/3D setting for participation of different clinicians in defining and validating surgical plans for SEEG cases.

Application of magnetic resonance fingerprinting to differentiate grade I transitional and fibrous meningiomas from meningothelial meningiomas

Background

The choice of surgical treatment for meningiomas is affected by the subtype and clinical characteristics. Therefore, an accurate preoperative diagnosis is essential. Current magnetic resonance imaging (MRI) technology is unable to distinguish between meningioma subtypes. In the present study, we compared and evaluated the utility of conventional MRI, magnetic resonance fingerprinting (MRF), and diffusion-weighted imaging (DWI) in differentiating World Health Organization grade I transitional and fibrous meningiomas from meningothelial meningiomas.

Methods

Forty-six patients with pathologically confirmed meningiomas (15 meningothelial, 18 transitional, and 13 fibrous) were enrolled in the present study. All patients underwent conventional MRI, MRF, and DWI scans before surgery using a 3T scanner. The Jonckheere-Terpstra test was used to analyze differences in the signal and enhancement characteristics of the three groups from T₁-weighted imaging (T1WI) and T₂-weighted imaging (T2WI). To investigate the difference in quantitative T1 and T2 values derived from MRF and apparent diffusion coefficient (ADC) values between the three groups using the Kruskal-Wallis test, regions of interest (ROIs) were manually drawn on the parenchymal portion of the tumors; P<0.017 was considered statistically significant after Bonferroni correction for multiple comparison. The receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performances of the different parameters.

Results

Meningothelial meningiomas had significantly higher T1 and T2 values than transitional and fibrous meningiomas (all P<0.017). ROC analysis results revealed that the combination of T1 and T2 values had the largest area under the curve (AUC). The AUC for the combination of T1 and T2 values was 0.826 between meningothelial and transitional meningiomas, and the AUC for the combination of T1 and T2 values between meningothelial and fibrous meningiomas was 0.903. No significant differences were found in the T1 and T2 values between transitional and fibrous meningiomas. There were also no statistically significant differences in the conventional MRI (including T1WI, T2WI, and contrast-enhanced T1WI) and ADC values between the three meningioma subtypes (all P>0.05).

Conclusions

MRF may provide more quantitative information than either conventional MRI or DWI for differentiating transitional and fibrous meningiomas from meningothelial meningiomas. T1 and T2 values derived from MRF may distinguish transitional and fibrous meningiomas from meningothelial meningiomas, and the combination of T1 and T2 values provides the highest diagnostic efficacy.

Noninvasive evaluation of diabetic patients with high fasting blood glucose using DWI and BOLD MRI

PURPOSE

To investigate the renal microstructure changes and hypoxia changes in type 2 diabetic patients and the relationship between them and glucose using both diffusion-weighted imaging (DWI) and blood oxygenation level-dependent magnetic resonance imaging (BOLD MRI).

METHODS

After measuring morning fasting blood glucose, DWI and BOLD MRI were performed in 57 patients with type 2 diabetes mellitus (DM group) and 14 healthy volunteers (NC group). According to the fasting blood glucose levels, diabetic patients were divided into a normoglycemic diabetes group (group A), a less hyperglycemic diabetes group (group B) and a more hyperglycemic diabetes group (group C). The renal parenchymal apparent diffusion coefficient (ADC), renal cortical R2* (CR2*), and medullary R2* (MR2*) were measured, and the R2* ratio between the medulla and cortex (MCR) was calculated. To test for differences in ADC, R2*, and MCR among the four groups, the data were analyzed by separate one-way ANOVAs. The correlations between ADC, R2*, and MCR and the clinical index of renal function were analyzed.

RESULTS

Groups B and C had significantly lower ADC values in the renal parenchyma (P = 0.048, 0.002) and significantly higher MR2* and MCR values (P < 0.000, P = 0.001, 0.001, and 0.005, respectively) than the NC group. ADC was negatively correlated with glucose, and MR2*, MCR and glucose showed a weak positive correlation.

CONCLUSION

DWI and BOLD may indirectly and qualitatively reflect the kidney microstructure status and hypoxia level of diabetic patients at different blood glucose levels to a certain extent, and possibly guide the clinical treatment of diabetic patients with different blood glucose levels.

Accuracy of whole-body diffusion-weighted MRI (WB-DWI/MRI) in diagnosis, staging and follow-up of gastric cancer, in comparison to CT: a pilot study

Background

Accurate staging of patients with gastric cancer is necessary for selection of the most appropriate and personalized therapy. Computed tomography (CT) is currently used as primary staging tool, being widely available with a relatively high accuracy for the detection of parenchymal metastases, but with low sensitivity for the detection of peritoneal metastases. Magnetic resonance imaging (MRI) with diffusion-weighted imaging (DWI) has a very high contrast resolution, suggesting a higher diagnostic performance in the detection of small peritoneal lesions. The aim of this study was to retrospectively evaluate the added value of whole-body diffusion-weighted MRI (WB-DWI/MRI) to CT for detection of peritoneal carcinomatosis (PC) and distant metastases in the preoperative staging of gastric cancer.

Methods

This retrospective study included thirty-two patients with a suspicion of gastric cancer/recurrence, who underwent WB-DWI/MRI at 1.5 T, in addition to CT of thorax and abdomen. Images were evaluated by two experienced abdominal radiologists in consensus. Histopathology, laparoscopy and/or 1-year follow-up were used as reference standard.

Results

For overall tumour detection (n = 32), CT sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) was 83.3%, 100%, 100% and 82.4% respectively. For WB-DWI/MRI these values were 100%, 92.9%, 94.7% and 100%, respectively. For staging (n = 18) malignant lymph nodes and metastases, CT had a sensitivity, specificity/PPV/NPV of 50%/100%/100%/71.4%, and 15.4%/100%/100%/31.3% respectively. For WB-DWI/MRI, all values were 100%, for both malignant lymph nodes and metastases. WB-DWI/MRI was significantly better than CT in detecting tumour infiltration of the mesenteric root, serosal involvement of the small bowel and peritoneal metastases for which WB-DWI/MRI was correct in 100% of these cases, CT 0%.

Conclusions

WB-DWI/MRI is highly accurate for diagnosis, staging and follow-up of patients with suspected gastric cancer.

Analysis of Renal Diffusion-Weighted Imaging (DWI) Using Apparent Diffusion Coefficient (ADC) and Intravoxel Incoherent Motion (IVIM) Models

Analysis of renal diffusion-weighted imaging (DWI) data to derive markers of tissue properties requires careful consideration of the type, extent, and limitations of the acquired data. Alongside data quality and general suitability for quantitative analysis, choice of diffusion model, fitting algorithm, and processing steps can have consequences for the precision, accuracy, and reliability of derived diffusion parameters. Here we introduce and discuss important steps for diffusion-weighted image processing, and in particular give example analysis protocols and pseudo-code for analysis using the apparent diffusion coefficient (ADC) and intravoxel incoherent motion (IVIM) models. Following an overview of general principles, we provide details of optional steps, and steps for validation of results. Illustrative examples are provided, together with extensive notes discussing wider context of individual steps, and notes on potential pitfalls.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concepts and experimental procedure.

Renal Diffusion-Weighted Imaging (DWI) for Apparent Diffusion Coefficient (ADC), Intravoxel Incoherent Motion (IVIM), and Diffusion Tensor Imaging (DTI): Basic Concepts

The specialized function of the kidney is reflected in its unique structure, characterized by juxtaposition of disorganized and ordered elements, including renal glomerula, capillaries, and tubules. The key role of the kidney in blood filtration, and changes in filtration rate and blood flow associated with pathological conditions, make it possible to investigate kidney function using the motion of water molecules in renal tissue. Diffusion-weighted imaging (DWI) is a versatile modality that sensitizes observable signal to water motion, and can inform on the complexity of the tissue microstructure. Several DWI acquisition strategies are available, as are different analysis strategies, and models that attempt to capture not only simple diffusion effects, but also perfusion, compartmentalization, and anisotropy. This chapter introduces the basic concepts of DWI alongside common acquisition schemes and models, and gives an overview of specific DWI applications for animal models of renal disease.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This introduction chapter is complemented by two separate chapters describing the experimental procedure and data analysis.

OKlahoma Nitrone-007: novel treatment for diffuse intrinsic pontine glioma

Background

Diffuse intrinsic pontine glioma (DIPG) is the most common brainstem cancer in childhood. This rapidly progressing brainstem glioma holds a very dismal prognosis with median survival of less than 1 year. Despite extensive research, no significant therapeutic advancements have been made to improve overall survival in DIPG patients.

Methods

Here, we used an orthotopic xenograft pediatric DIPG (HSJD-DIPG-007) mouse model to monitor the effects of anti-cancer agent, OKlahoma Nitrone-007 (OKN-007), as an inhibitor of tumor growth after 28 days of treatment. Using magnetic resonance imaging (MRI), we confirmed the previously described efficacy of LDN-193189, a known activin A receptor, type I (ACVR1) inhibitor, in decreasing tumor burden and found that OKN-007 was equally efficacious.

Results

After 28 days of treatment, the tumor volumes were significantly decreased in OKN-007 treated mice (p < 0.01). The apparent diffusion coefficient (ADC), as a measure of tissue structural alterations, was significantly decreased in OKN-007 treated tumor-bearing mice (p < 0.0001). Histological analysis also showed a significant decrease in CD34 expression, essential for angiogenesis, of OKN-007 treated mice (p < 0.05) compared to LDN-193189 treated mice. OKN-007-treated mice also significantly decreased protein expression of the human nuclear antigen (HNA) (p < 0.001), ACVR1 (p < 0.0001), and c-MET (p < 0.05), as well as significantly increased expression of cleaved caspase 3 (p < 0.001) and histone H3 K27-trimethylation (p < 0.01), compared to untreated mouse tumors.

Conclusions

With the dismal prognosis and limited effective chemotherapy available for DIPG, there is significant room for continued research studies, and OKN-007 merits further exploration as a therapeutic agent.

The value of bi-exponential and non-Gaussian distribution diffusion-weighted imaging in the differentiation of recurrent soft tissue neoplasms and post-surgical changes

Background

Many researches focused on the quantitative mono-exponential diffusion-weighted imaging (DWI) in the assessment of soft tissue neoplasms (STN), but few focused on the value of bi-exponential and non-Gaussian DWI in the application of Recurrent Soft Tissue Neoplasms (RSTN). This study aimed to explore the feasibility of bi-exponential decay and non-Gaussian distribution DWI in the differentiation of RSTN and Post-Surgery Changes (PSC), and compared with mono-exponential DWI.

Methods

The clinical, mono-exponential, bi-exponential [intravoxel incoherent motion (IVIM)] and non-Gaussian [diffusion kurtosis imaging (DKI)] DWI imaging of a cohort of 27 patients [15 RSTN (22 masses), and 12 PSC (12 lesions)] with 34 masses, from Nov 01 2017 to Sep 30 2018, were reviewed. The differences of apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), mean diffusivity (MD), and mean kurtosis (MK) values were compared between RSTN and PSC groups. The mono-, bi-exponential, and non-Gaussian distribution based predictive models for RSTN and PSC were built and compared. ROC curves were generated and compared by the DeLong test.

Results

Intra-class correlation coefficient (ICC) of all IVIM/DKI parameters was high (≥0.841). There were significant differences in ADC, D, f, MD, and MK values between RSTN and PSC, but no difference in D* value. The ADC_IVIM, D, f and MD values of RSTN were lower than those of PSC, but with higher MK value. The ADC_IVIM and D values did better than f value in differentiating these two groups (P<0.05). While there was no significant difference in AUCs among ADC_DKI, MD, and MK values. Also, no significant difference was detected in AUCs between bi-exponential and mono-exponential (P=0.38), or between mono-exponential and non-Gaussian distribution based prediction models (P=0.09).

Conclusions

ADC, D, f, MD, and MK values can be used in the differentiation of RSTN and PSC.

Apparent diffusion coefficient value of mass-forming intrahepatic cholangiocarcinoma: a potential imaging biomarker for prediction of lymph node metastasis

PURPOSE

To compare the differences of MR features between mass-forming intrahepatic cholangiocarcinoma (IMCC) with and without lymph node metastasis (LNM) and to search for new imaging biomarkers for predicting LNM.

MATERIALS AND METHODS

The study included 91 patients with histopathologically confirmed single IMCC (20 patients with LNM and 71 patients without LNM). Findings of preoperative MR imaging including diffusion-weighted imaging (DWI) (b value 0, 500 mm²/s) were analyzed and apparent diffusion coefficient (ADC) values (b = 500 mm²/s) were calculated. Logistic regression analysis was performed to identify independent predictors of LNM. The diagnostic performance of independent predictors was assessed by receiver operating characteristic (ROC) and area under the curve (AUC) was compared.

RESULTS

Larger tumor size (p = 0.001), diameter of largest lymph node (LN) > 1 cm (p < 0.001), higher ADC value of primary IMCC lesion (ADC_IMCC value) (p = 0.001), and positive CA19-9 level (p = 0.018) were correlated with LNM. Multivariate logistic regression analysis demonstrated that ADC_IMCC value (odds ratio, 3.347; p = 0.001) and diameter of largest LN > 1 cm (odds ratio, 7.571; p = 0.004) were independent predictors of LNM. The AUCs for ADC_IMCC value, diameter of largest LN > 1 cm,and combined method (the combination of ADC_IMCC value and diameter of largest LN > 1 cm) were 0.782, 0.701,and 0.857, respectively. The AUC for combined method was significantly higher than that of diameter of largest LN > 1 cm (p = 0.033).

CONCLUSION

ADC_IMCC value can be a potential imaging biomarker for predicting LNM of IMCC, especially in combination with diameter of largest LN > 1 cm.

Diffusion MR Imaging in the Head and Neck: Principles and Applications

Diffusion imaging is a functional MR imaging tool that creates tissue contrast representative of the random, microscopic translational motion of water molecules within human body tissues. Long considered a cornerstone MR imaging sequence for brain imaging, diffusion-weighted imaging (DWI) increasingly is used for head and neck imaging. This review reports the current state of diffusion techniques for head and neck imaging, including conventional DWI, DWI trace with apparent diffusion coefficient map, diffusion tensor imaging, intravoxel incoherent motion, and diffusion kurtosis imaging. This article describes background physics, reports supportive evidence and potential pitfalls, highlights technical advances, and details practical clinical applications.

Quantitative assessment of renal allograft pathologic changes: comparisons of mono-exponential and bi-exponential models using diffusion-weighted imaging

Background

Diffusion-weighted imaging (DWI) can noninvasively assess renal allograft pathologic changes that provide useful information for clinical management and prognostication. However, it is still unknown whether the bi-exponential model analysis of DWI signals is superior to that of the mono-exponential model.

Methods

Pathologic and DWI data from a total of 47 allografts were prospectively collected and analyzed. Kidney transplant interstitial fibrosis was quantified digitally. The severity of acute and chronic pathologic changes was semi-quantified by calculating the acute composite scores (ACS) and chronic composite score (CCS). Mono-exponential total apparent diffusion coefficient (ADCT), and the bi-exponential parameters of true diffusion (D) and perfusion fraction (fp) were acquired. The diagnostic performances of both mono-exponential and bi-exponential parameters were assessed and compared by calculating the area under the curve (AUC) from receiver-operating characteristic (ROC) curve analysis.

Results

ADCT, D, and fp were all significantly correlated with interstitial fibrosis, ACS, and CCS. Cortical fp discriminated mild from moderate and severe ACS with the largest AUC of 0.89 [95% confidence interval (CI), 0.77-0.96]. Noticeably, only cortical fp could differentiate severe ACS from mild-to-moderate ACS (P<0.001) with an AUC of 0.80 (95% CI, 0.65-0.90) and a sensitivity of 100% (95% CI, 66.4-100%). Strikingly, the joint use of D and fp in either the cortex or the medulla could achieve a sensitivity of 100% for identifying either mild or severe interstitial fibrosis. Meanwhile, the serial use of cortical D and cortical fp showed the largest specificity for identifying both mild [88.9% (95% CI, 70.8-97.6%)] and severe [84.4% (95% CI, 67.2-94.7%)] interstitial fibrosis. For identifying mild CCS, the AUC of medullary ADCT (0.90, 95% CI, 0.78-0.97) was similar to that of cortical D (0.81, 95% CI, 0.67-0.91) and fp (0.86, 95% CI, 0.73-0.94), but statistically larger than that of medullary D (P=0.005) and fp (P=0.01). Furthermore, the parallel use of cortical D and cortical fp could increase the sensitivity to 95.0% (95% CI, 75.1-99.9%), whereas serial use of medullary D and medullary fp could increase the specificity to 100% (95% CI, 87.2-100%). The AUCs for differentiating severe from mild and moderate CCS were statistically insignificant among all parameters in the cortex and medulla (P≥0.15).

Conclusions

Cortical fp was superior to the ADCT for identifying both mild and severe acute pathologic changes. Nevertheless, ADCT was equal to or better than single D or fp for evaluating chronic pathologic changes. Thus, both monoexponential and bi-exponential analysis of DWI images are complementary for evaluating kidney allograft pathologic changes, and the combined use of D and fp can increase the sensitivity and specificity for discriminating allograft pathologic changes severity.

A case of CLCN2-related leukoencephalopathy with bright tree appearance during aseptic meningitis

CLCN2-related leukoencephalopathy (CC2L) is a rare autosomal recessive disorder caused by variants in CLCN2. We report a boy whose brain MRI during an episode of aseptic meningitis at the age of 6 years revealed wide areas of restriction on diffusion-weighted images (DWI) in the cerebral subcortical white matter called bright tree appearance (BTA). In addition to the BTA, high intensity signals were also observed bilaterally in the posterior limbs of the internal capsules, cerebral peduncles, middle cerebellar peduncles, cerebellar white matter, and brain stem (longitudinal pontine bundle) along with low apparent diffusion coefficient values in the same areas. The BTA was transient, seen only during the acute phase of the aseptic meningitis. With the resolution of the infection, his meningitis symptoms completely resolved, but abnormal brain MRI findings remained, other than BTA, which disappeared. At age 13 years, whole exome sequencing revealed a homozygous variant (c.61dupC, p.(Leu21Profs*27)) of CLCN2. He had no intellectual disability or neurological abnormalities. The transient DWI high-intensity signals in the subcortical white matter and the T2 high-intensity signals in the white matter could reflect varying degrees of water imbalance in the extracellular space in myelin sheaths in CC2L.

Impact of stroke volume on motor outcome in neonatal arterial ischemic stroke

BACKGROUND AND OBJECTIVES

Neonatal arterial ischemic stroke (NAIS) can lead to long-term neurological consequences such as cerebral palsy (CP). The aim of this study was to evaluate the predictive value of acute diffusion-weighted imaging (DWI) for CP by analyzing stroke volume next to brain structure involvement.

METHODS

We included 37 term-born infants with NAIS prospectively registered in a nationwide pediatric stroke registry. DWI was performed between 0 and 8 days (mean 3 days) after stroke manifestation. Participants were neurologically assessed at the age of 2 years. We calculated the stroke volume (in mm³) and the ratio of the stroke volume to the volume of the entire brain (relative stroke volume). The predictive value of the relative stroke volume was analyzed and an optimal threshold for classification of children with high- and low-rates of CP was calculated. Predictive value of brain structure involvements and the prevalence of CP in combinations of different brain structures was also assessed.

RESULTS

Sixteen children (43.2%) developed CP. Relative stroke volume significantly predicted CP (p < .001). Its optimal threshold for division into high- and low-rate of CP was 3.3%. The basal ganglia (OR 8.3, 95% CI 1.2-60.0) and basis pontis (OR 18.5, 95% CI 1.8-194.8) were independently associated with CP.

CONCLUSION

In addition to determining the involvement of affected brain areas, the volumetric quantification of stroke volume allows accurate prediction of cerebral palsy in newborns with NAIS.

Apparent diffusion coefficient value of mass-forming intrahepatic cholangiocarcinoma: a potential imaging biomarker for prediction of lymph node metastasis

PURPOSE

To compare the differences of MR features between mass-forming intrahepatic cholangiocarcinoma (IMCC) with and without lymph node metastasis (LNM) and to search for new imaging biomarkers for predicting LNM.

MATERIALS AND METHODS

The study included 91 patients with histopathologically confirmed single IMCC (20 patients with LNM and 71 patients without LNM). Findings of preoperative MR imaging including diffusion-weighted imaging (DWI) (b value 0, 500 mm²/s) were analyzed and apparent diffusion coefficient (ADC) values (b = 500 mm²/s) were calculated. Logistic regression analysis was performed to identify independent predictors of LNM. The diagnostic performance of independent predictors was assessed by receiver operating characteristic (ROC) and area under the curve (AUC) was compared.

RESULTS

Larger tumor size (p = 0.001), diameter of largest lymph node (LN) > 1 cm (p < 0.001), higher ADC value of primary IMCC lesion (ADC_IMCC value) (p = 0.001), and positive CA19-9 level (p = 0.018) were correlated with LNM. Multivariate logistic regression analysis demonstrated that ADC_IMCC value (odds ratio, 3.347; p = 0.001) and diameter of largest LN > 1 cm (odds ratio, 7.571; p = 0.004) were independent predictors of LNM. The AUCs for ADC_IMCC value, diameter of largest LN > 1 cm,and combined method (the combination of ADC_IMCC value and diameter of largest LN > 1 cm) were 0.782, 0.701,and 0.857, respectively. The AUC for combined method was significantly higher than that of diameter of largest LN > 1 cm (p = 0.033).

CONCLUSION

ADC_IMCC value can be a potential imaging biomarker for predicting LNM of IMCC, especially in combination with diameter of largest LN > 1 cm.

Current status and recommendations for imaging in neurofibromatosis type 1, neurofibromatosis type 2, and schwannomatosis

Neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN) are three clinically distinct tumor predisposition syndromes with a shared tendency to develop peripheral and central nervous system neoplasms. Disease expression and complications of NF1, NF2, and SWN are highly variable, necessitating a multidisciplinary approach to care in order to optimize outcomes. This review will discuss the imaging appearance of NF1, NF2, and SWN and highlight the important role that imaging plays in informing management decisions in people with tumors associated with these syndromes. Recent technological advances, including the role of both whole-body and localized imaging strategies, routine anatomic and advanced magnetic resonance (MR) imaging sequences such as diffusion-weighted imaging (DWI) with quantitative apparent diffusion coefficient (ADC) mapping, and metabolic imaging techniques (MR spectroscopy and positron emission testing) are discussed in the context of the diagnosis and management of people with NF1, NF2, and SWN based on the most up-to-date clinical imaging studies.

Auditory prediction errors and auditory white matter microstructure associated with psychotic-like experiences in healthy individuals

Our sensory systems actively predict sensory information based on previously learnt patterns, which are continuously updated with information from the actual sensory input via prediction errors. Individuals with schizophrenia consistently show reduced auditory prediction errors as well as altered fractional anisotropy (indicative of white matter changes) in the arcuate fasciculus and the auditory interhemispheric pathway, both of which are auditory white matter pathways associated with prediction errors. However, it is not clear if healthy individuals with psychotic-like experiences exhibit similar deficits. Participants underwent electroencephalography (EEG) recordings while listening to a classical two-tone duration deviant oddball paradigm (n = 103) and a stochastic oddball paradigm (n = 89). A subset of participants (n = 89) also underwent diffusion-weighted magnetic resonance imaging (MRI). Fractional anisotropy (FA), was extracted from the arcuate fasciculi and the auditory interhemispheric pathway. While prediction errors evoked by the classical oddball paradigm failed to reveal significant effects, the stochastic oddball paradigm elicited significant clusters at the typical mismatch negativity time window. Furthermore, we observed that FA of the arcuate fasciculi and auditory interhemispheric pathway significantly improved predictive models of psychotic-like experiences in healthy individuals over and above predictions made by auditory prediction error responses alone. Specifically, we observed that decreasing FA in the auditory interhemispheric pathway and reducing ability to learn stochastic irregularities are associated with increasing CAPE + scores. To the extent that these associations have previously been reported in patients with schizophrenia, the findings from this study suggest that both, auditory prediction errors and white matter changes in the auditory interhemispheric pathway, may have the potential to be translated into early screening markers for psychosis.

Intravoxel incoherent motion MR imaging for differentiating malignant lesions in spine: A pilot study

PURPOSE

To determine the diagnostic potential of Intravoxel Incoherent Motion (IVIM) MRI for differentiating malignant spinal tumours from acute vertebral compression fractures and tuberculous spondylitis, and to compare IVIM with diffusion-weighted imaging (DWI) and chemical shift imaging (CSI).

METHODS

The Institutional Review Board approved this prospective study, and informed consent was obtained. IVIM MRI, DWI, and CSI at 1.5 T were performed in 25 patients with 12 acute compression fractures, 14 tuberculous spondylitis, and 18 malignant spinal tumours. The parameters of these techniques were assessed using the Kruskal-Wallis test. The diagnostic performance of the parameters was evaluated using receiver operating characteristic (ROC) analysis.

RESULTS

ADC, SIR, D_slow, D_fast, and f values of malignant tumours were significantly different from those of acute compression fracture (for all, p < 0.05). The mean D_slow and D_fast values of malignant spinal tumours had significant differences compared with those of tuberculous spondylitis (for all, p < 0.05). However, no significant differences were observed in any quantitative parameters between the acute compression fracture and the tuberculous spondylitis (p > 0.05). D_slow•f showed the highest AUC value of 0.980 (95%CI: 0.942-1.000) in differentiating acute compression fracture and malignant spinal tumours. D_slow showed the highest AUC value of 0.877 (95%CI: 0.713-0.966) in differentiating tuberculous spondylitis and malignant spinal tumours.

CONCLUSIONS

IVIM MR imaging may be helpful for differentiating malignant spinal tumours from acute vertebral compression fractures and tuberculous spondylitis.

A multiparametric analysis based on DCE-MRI to improve the accuracy of parotid tumor discrimination

BACKGROUND

Recently, semiquantitative time-intensity curve (TIC) analysis based on DCE-MRI and apparent diffusion coefficient (ADC) value-based diffusion-weighted imaging (DWI) were used to improve the diagnostic efficiency when diagnosing parotid tumors (PTs). However, quantitative DCE-MRI biomarkers have not been emphasized previously.

PURPOSE

To explore the diagnostic efficiency of perfusion parameters alone or in combination based on quantitative DCE-MRI and DWI in the differential diagnosis of PTs.

METHODS

In total, 112 patients with parotid masses were prospectively recruited in our hospital from August 2013 to March 2017. All patients were evaluated with DCE-MRI and DWI before surgery. TIC and quantitative parameters based on DCE MRI and ADCs were analyzed. Receiver operating characteristic analysis and linear discriminant analysis (LDA) was used to determine their diagnostic performance.

RESULTS

In total, 87% (27/31) of pleomorphic adenoma (PA) showed type A TIC, 74% (65/88) of Warthin's tumors showed type B TIC, and 95% (19/20) of malignant tumors showed TIC type C. Pearson X² test showed a significant difference between TIC patterns in benign and malignant tumors (X² = 38.78, p < 0.001). ROC analysis revealed that ADC achieved the best diagnostic performance for distinguishing PA and Warthin's tumor from others, with area under the curve (AUC) values of 0.945 and 0.925 (p < 0.01), respectively. Furthermore, the TIC type was the only useful biomarker for distinguishing malignant from benign PTs, with an AUC of 0.846 (p < 0.01). Concerning the accuracy of the combined application of multiple parameters of DCE-MRI and ADC values, a combination of TIC pattern and extracellular volume ratio (Ve) provided the best results among five protocols, producing the highest accuracy of 0.75, followed by the combined use of the TIC pattern and ADC (accuracy was 0.70).

CONCLUSION

TIC pattern in combination with the Ve biomarker based on DCE-MRI could achieve optimal diagnostic accuracy in the differential diagnosis of PTs.

Diffusion-weighted imaging as a part of PET/MR for small lesion detection in patients with primary abdominal and pelvic cancer, with or without TOF reconstruction technique

OBJECTIVES

To investigate the value of diffusion-weighted imaging (DWI) in detection of small lesions (≤ 10 mm) in patients with primary abdominal and pelvic cancer in hybrid PET/MR with or without time-of-flight (TOF) technique.

MATERIALS AND METHODS

Twenty patients (11 females and 9 males, mean age 67.23 ± 12.90 years) with histologically confirmed primary abdominal and pelvic cancer underwent hybrid PET/MR examination. A total of 64 small lesions were included in this study, which were divided into two groups (≤ 10 mm and 10-30 mm). Visual scores of small lesion detection ability were rated by five-point ordinal scale. The visual scores and detectability of small lesions on TOF PET image, noTOF PET image, and DWI sequences of hybrid PET/MR examination with or without TOF technique were analyzed. Logistic regression model was established for analysis in the value of DWI in hybrid PET/MR examination with or without TOF technique in detection of the small lesions between two groups.

RESULTS

The visual evaluation revealed the small lesion (≤ 10 mm) visual scores of DWI (mean ± SD: 4.23 ± 1.41), TOF PET image (mean ± SD: 4.14 ± 0.89), and noTOF PET image (mean ± SD: 2.68 ± 1.13);.and the visual scores of small lesions (10-30 mm) on DWI (mean ± SD: 4.98 ± 0.15), TOF PET image (mean ± SD: 4.57 ± 0.59), and noTOF PET image (mean ± SD: 3.98 ± 1.05). The visual scores of all small lesions on DWI were higher than that on TOF PET data and noTOF PET data in both two groups (**P < 0.01). The missed diagnosis rates of small FDG avid lesions (≤ 10 mm) of DWI and noTOF PET image were 9.1% and 9.1%, respectively. However, the TOF PET-based clinical diagnosis detected all small lesions (≤ 30 mm). DWI was of great importance in detection of small lesions (≤ 10 mm) in the absence of TOF technique in PET/MR examination (**P < 0.01). DWI's effect on detection of small lesions(10-30 mm) has shown no difference between PET/MR examinations with TOF and without TOF techniques (P > 0.05).

CONCLUSION

DWI has significant value in the detection of small lesions (≤ 10 mm) in hybrid PET/MR examination without TOF technique for patients with primary abdominal and pelvic cancer. However, it had less detection benefits in the small lesions (≤ 10 mm) in hybrid PET/MR examination with TOF PET image.

Effects of region of interest sizes on apparent diffusion coefficient measurements of pleomorphic adenoma, Warthin tumor, and normal parotid parenchyma

Background

Tumor apparent diffusion coefficient (ADC) measurements may be influenced by region of interest (ROI) sizes; however, this effect has not been systematically studied in parotid tumors. Our purpose was to determine the effects of ROI size on ADC measurements for the differentiation of pleomorphic adenoma (PA), Warthin tumor (WT), and normal parotid parenchyma.

Methods

Sixty-five patients including 37 with PA (lesions, n=37) and 28 with WT (lesions, n=36) were examined with diffusion-weighted imaging (DWI). Participants with normal contralateral parenchyma of the parotid gland constituted the control group (n=56). The mean ADC values and standard deviations (SDs) of the ADC (ADC_SD) of 12 concentric round ROIs (areas: 9, 28, 34, 50, 60, 82, 93, 98, 115, 130, 136, and 149 mm²) for tumors and normal tissue were measured by using custom-made software. Homogeneity index, which was defined by the ADC_SD/mean ADC, was also calculated. One-way repeated analyses of variance (ANOVAs) were performed on the mean ADCs, ADC_SDs, and homogeneity indices of the 12 ROIs in each group. The three parameters at different ROIs among PA, WT, and normal parotid parenchyma were compared using Kruskal-Wallis tests.

Results

There was excellent agreement for the ADC measurements with the 12 ROIs for PA [intraclass correlation coefficient (ICC), 0.98], WT (ICC, 0.99), and normal parotid parenchyma (ICC, 0.95). No significant differences were observed in the mean ADCs of the 12 ROIs for each of the three groups (P=0.744-0.990). Among the three groups, the mean ADC of normal parotid parenchyma [(0.94±0.003)×10^-3 mm²/s] was significantly lower than that of both PA [(1.72±0.01)×10^-3 mm²/s] and WT [(1.16±0.01)×10^-3 mm²/s] in the 12 ROIs, whereas the PA group had the highest mean ADC values. No significant differences were found in the mean ADC_SDs with each ROI between PA and WT (all P>0.017). PAs had lower homogeneity indices compared with WTs and normal parotid parenchyma (all P<0.01).

Conclusions

The effect of ROI size on ADC measurements could be excluded from the differentiation of PA, WT, and normal parotid parenchyma. Homogeneity index was a useful parameter in discriminating between the three groups.

Volumetric quantitative histogram analysis using diffusion-weighted magnetic resonance imaging to differentiate HCC from other primary liver cancers

OBJECTIVE

To evaluate the ability of volumetric quantitative apparent diffusion coefficient (ADC) histogram parameters and LI-RADS categorization to distinguish hepatocellular carcinoma (HCC) from other primary liver cancers [intrahepatic cholangiocarcinoma (ICC) and combined HCC-ICC].

METHODS

Sixty-three consecutive patients (44 M/19F; mean age 62 years) with primary liver cancers and pre-treatment MRI including diffusion-weighted imaging (DWI) were included in this IRB-approved single-center retrospective study. Tumor type was categorized pathologically. Qualitative tumor features and LI-RADS categorization were assessed by 2 independent observers. Lesion volume of interest measurements (VOIs) were placed on ADC maps to extract first-order radiomics (histogram) features. ADC histogram metrics and qualitative findings were compared. Binary logistic regression and AUROC were used to assess performance for distinction of HCC from ICC and combined tumors.

RESULTS

Sixty-five lesions (HCC, n = 36; ICC, n = 17; and combined tumor, n = 12) were assessed. Only enhancement pattern (p < 0.015) and capsule were useful for tumor diagnosis (p < 0.014). ADC 5th/10th/95th percentiles were significant for discrimination between each tumor types (all p values < 0.05). Accuracy of LI-RADS for HCC diagnosis was 76.9% (p < 0.0001) and 69.2% (p = 0.001) for both observers. The combination of male gender, LI-RADS, and ADC 5th percentile yielded an AUROC/sensitivity/specificity/accuracy of 0.90/79.3%/88.9%/81.5% and 0.89/86.2%/77.8%/80.0% (all p values < 0.027) for the diagnosis of HCC compared to ICC and combined tumors for both observers, respectively.

CONCLUSION

The combination of quantitative ADC histogram parameters and LI-RADS categorization yielded the best prediction accuracy for distinction of HCC compared to ICC and combined HCC-ICC.

Application of diffusion-weighted MR imaging with ADC measurement for distinguishing between the histopathological types of sinonasal neoplasms

PURPOSE

To evaluate the potential contribution of quantitative DWI parameters including ADC_mean and ADC_ratio values to help in distinguishing the histopathological types of sinonasal neoplasms.

METHODS

This retrospective study included 83 patients (50 males, 33 females; mean age 61 years) with pathologically proven untreated sinonasal neoplasms who have undergone diffusion-weighted MRI imaging from February 2010 to August 2017. Diffusion-weighted MRI was performed on a 3 T unit with b factors of 0 and 1000 s/mm², and ADC maps were generated. Mean ADC values of sinonasal tumors and ADC ratios (ADC_mean of the tumor to ADC_mean of pterygoid muscles) were compared with the histopathological diagnosis by utilizing the Kruskal-Wallis non-parametric test.

RESULTS

Mean ADC_mean and ADC_ratio were 0.8 (SD, ±0.4) × (10^-3 mm²/s) and 1.2 (SD, ±0.5), respectively, and each parameter was significantly different between histopathological types (p < 0.05). Mean ADC_mean and ADC_ratio were higher in adenoid cystic carcinoma (ACC) than in SCC, lymphoma, neuroendocrine carcinoma and sinonasal undifferentiated carcinoma (SNUC) (p < 0.05). Optimized ADC_mean thresholds of 0.79, 0.81, 0.74 and 0.78 (10^-3 mm²/s) achieved maximal discriminatory accuracies of 100%, 79%, 100% and 89% for ACC/SNUC, ACC/SCC, ACC/neuroendocrine carcinoma, and ACC/lymphoma, respectively.

CONCLUSIONS

The optimized ADC_mean threshold of 0.80 (10^-3 mm²/s) could be used to differentiate ACC from non-ACC sinonasal neoplasms with maximal discriminatory accuracy (82%) and sensitivity of 100%. However, there is considerable overlapping of the ADC_mean and ADC_ratio values among non-ACC sinonasal neoplasms hence surgical biopsy is still needed.

Diversity of imaging features of ovarian sclerosing stromal tumors on MRI and PET-CT: a case report and literature review

Background

Sclerosing stromal tumors (SST) are rare, benign tumors classified as sex cord stromal tumors. To our knowledge, positron emission tomography with computed tomography (PET-CT) findings of SST have only been described in one report and imaging findings on diffusion-weighted imaging (DWI) have only been described in three reports. Characteristic imaging features of SST on PET-CT and DWI have not yet been identified. Here we report a case of multilocular SST with solid components showing mild FDG uptake and slight hyperintensity on DWI, and reviewed the literature.

Case presentation

Seventeen-year-old woman presented with a complaint of abdominal pain and was admitted due to infectious colitis. Ultrasonography incidentally revealed a multiseptated cystic mass in the pelvis. Magnetic resonance imaging (MRI) showed a large multilobulated cystic mass with irregularly thickened septa and solid components originating in the left adnexa. On T2WI, the cystic components had the same signal intensity (SI) as water, and the irregularly thickened septa and solid components showed intermediate SI higher than the SI of the uterine myometrium. The septa and solid components also showed early strong enhancement on contrast-enhanced T1WI and slight hyperintensity on DWI. The PET-CT showed mild FDG uptake in the solid components of the tumor (SUV: 2.11). According to previous articles, the morphology of SSTs are various; solid mass, well-circumscribed multilobular mass, well-demarcated mass, and multilocular cysticmass. According to the reports describing DWI findings of SST, the SI varies from significant hyperintensity to slightly hyperintensity like in this case. Only one report describing PET-CT findings of SST showed intense FDG uptake (SUV max: 7.0).

Conclusion

The findings on DWI and PET-CT of our case and the past reports describing PET and DWI findings of SSTs are not consistent. The wide variety of the signal intensity on MRI and FDG uptake on PET could be due to the pathological diversity caused by the cellular areas undergoing collagenous sclerosis, which transforms the tumor into admixture of the collagen and the densely fibrous components with edema.

Diffusion-weighted MR imaging of locally advanced breast carcinoma: the optimal time window of predicting the early response to neoadjuvant chemotherapy

Background

It is very difficult to predict the early response to NAC only on the basis of change in tumor size. ADC value derived from DWI promises to be a valuable parameter for evaluating the early response to treatment. This study aims to establish the optimal time window of predicting the early response to neoadjuvant chemotherapy (NAC) for different subtypes of locally advanced breast carcinoma using diffusion-weighted imaging (DWI).

Methods

We conducted an institutional review board-approved prospective clinical study of 142 patients with locally advanced breast carcinoma. All patients underwent conventional MR and DW examinations prior to treatment and after first, second, third, fourth, sixth and eighth cycle of NAC. The response to NAC was classified into a pathologic complete response (pCR) and a non-pCR group. DWI parameters were compared between two groups, and the optimal time window for predicting tumor response was established for each chemotherapy regimen.

Results

For all the genomic subtypes, there were significant differences in baseline ADC value between pCR and non-pCR group (p < 0.05). The time point prior to treatment could be considered as the ideal time point regardless of genomic subtype. In the group that started with taxanes or anthracyclines, for Luminal A or Luminal B subtype, postT1 could be used as the ideal time point during chemotherapy; for Basal-like or HER2-enriched subtype, postT2 as the ideal time point during chemotherapy. In the group that started with taxanes and anthracyclines, for HER2-enriched, Luminal B or Basal-like subtype, postT1 could be used as the ideal time point during chemotherapy; for Luminal A subtype, postT2 as the ideal time point during chemotherapy.

Conclusions

The time point prior to treatment can be considered as the optimal time point regardless of genomic subtype. For each chemotherapy regimen, the optimal time point during chemotherapy varies across different genomic subtypes.

Diffusion-weighted imaging (DWI) in lymph node staging for prostate cancer

In patients with prostate cancer, the presence of lymph node (LN) metastases is a critical prognostic factor and is essential for treatment planning. Conventional cross-sectional imaging performs poorly for nodal staging as both computed tomography (CT) and magnetic resonance imaging (MRI) are mainly dependent on size and basic morphological criteria. Therefore, extended pelvic LN dissection (ePLND) remains the gold standard for LN staging, however, it is an invasive procedure with its own drawbacks, thus creating a need for accurate preoperative imaging test. Incorporating functional MRI by using diffusion-weighted MRI has proven superior to conventional MRI protocol by means of both qualitative and quantitative assessment. Currently, the increased diagnostic performance remains insufficient to replace ePLND and the future role of DWI may be through combination with MR lymphangiography or with novel positron emission tomography (PET) tracers. In this article, the current state of data supporting DWI in LN staging of patients with prostate cancer is discussed.

Intravoxel incoherent motion (IVIM) at 3.0 T: evaluation of early renal function changes in type 2 diabetic patients

PURPOSE

The purpose of this study was to evaluate the utility of intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) parameters in identifying early renal function changes in diabetics.

METHODS

A total of 40 patients with type 2 diabetes mellitus and 20 healthy control subjects underwent multiple b value DWI. The diabetic patients were stratified into two groups based on albuminuria category: NAU (normal to mildly increased albuminuria; ACR < 30 mg/g) and MAU (moderately increased albuminuria; 30 ≤ ACR < 300 mg/g). The mean cortical and medullary IVIM parameters (D, D*, f, and ADC) were calculated and compared among the different groups, and the correlation of ACR and eGFR was also calculated.

RESULTS

The present study revealed the limited water molecule diffusion and hyperperfusion of renal cortex and medulla in diabetic patients before proteinuria detection. Mean cortical and medullary D values negatively correlated with the ACR values in diabetics with 30 ≤ ACR < 300 mg/g, whereas no correlation was found between ACR values and other IVIM parameters.

CONCLUSION

IVIM DWI might be helpful in noninvasively identifying early-stage DN. The IVIM parametric values are more sensitive than the ACR in detecting early-stage kidney changes.

[Renal functional diagnostics using magnetic resonance imaging]

Due to progress in the development of sequences and techniques magnetic resonance imaging (MRI) methods, such as functional MR urography (fMRU), arterial spin labeling (ASL), diffusion-weighted imaging (DWI), diffusion tension imaging (DTI) and blood oxygen level dependent MRI (BOLD-MRI) have become available for renal functional evaluation. In recent years research of these imaging techniques has demonstrated that they provide valid functional data with respect to renal perfusion, oxygenation and interstitial diffusion as well as glomerular filtration and the extent of an obstructive uropathy. Many pathophysiological renal processes, e. g. in transplanted kidneys, in the setting of chronic kidney disease and in the diagnostics of renal tumors, can therefore be fully evaluated. The fMRU, which enables a reliable assessment of renal function combined with high-resolution morphological evaluation of the kidneys and the entire urinary tract, has already become an inherent component in the clinical setting, at least in specialized pediatric radiology centers. To establish the new imaging methods in the clinical routine, further technical improvements and large-scale prospective clinical studies are necessary to validate the determined functional parameters, to generate standard protocols and to unify and facilitate data post-processing.

Apparent diffusion coefficient (ADC) does not correlate with different serological parameters in myositis and myopathy

Background Magnetic resonance imaging (MRI) is widely used in several muscle disorders. Diffusion-weighted imaging (DWI) is an imaging modality, which can reflect microstructural tissue composition. The apparent diffusion coefficient (ADC) is used to quantify the random motion of water molecules in tissue. Purpose To investigate ADC values in patients with myositis and non-inflammatory myopathy and to analyze possible associations between ADC and laboratory parameters in these patients. Material and Methods Overall, 17 patients with several myositis entities, eight patients with non-inflammatory myopathies, and nine patients without muscle disorder as a control group were included in the study (mean age = 55.3 ± 14.3 years). The diagnosis was confirmed by histopathology in every case. DWI was obtained in a 1.5-T scanner using two b-values: 0 and 1000 s/mm². In all patients, the blood sample was acquired within three days to the MRI. The following serological parameters were estimated: C-reactive protein, lactate dehydrogenase, alanine aminotransferase, aspartate aminotransferase, creatine kinase, and myoglobine. Results The estimated mean ADC value for the myositis group was 1.89 ± 0.37 × 10^-3mm²/s and for the non-inflammatory myopathy group was 1.79 ± 0.33 × 10^-3 mm²/s, respectively. The mean ADC values (1.15 ± 0.37 × 10^-3 mm²/s) were significantly higher to unaffected muscles (vs. myositis P = 0.0002 and vs. myopathy P = 0.0021). There were no significant correlations between serological parameters and ADC values. Conclusion Affected muscles showed statistically significantly higher ADC values than normal muscles. No linear correlations between ADC and serological parameters were identified.

Value of diffusion-weighted imaging for monitoring tissue change during magnetic resonance-guided high-intensity focused ultrasound therapy in bone applications: an ex-vivo study

BACKGROUND

Magnetic resonance (MR)-guided high-intensity focused ultrasound (HIFU) can palliate metastatic bone pain by periosteal neurolysis. We investigated the value of diffusion-weighted imaging (DWI) for monitoring soft tissue changes adjacent to bone during MR-guided HIFU. We evaluated the repeatability of the apparent diffusion coefficient (ADC) measurement, the temporal evolution of ADC change after sonication, and its relationship with thermal parameters.

METHODS

Ex-vivo experiments in lamb legs (n = 8) were performed on a Sonalleve MR-guided HIFU system. Baseline proton resonance frequency shift (PRFS) thermometry evaluated the accuracy of temperature measurements and tissue cooling times after exposure. PRFS acquired during sonication (n = 27) was used to estimate thermal dose volume and temperature. After repeat baseline measurements, DWI was assessed longitudinally and relative ADC changes were derived for heated regions.

RESULTS

Baseline PRFS was accurate to 1 °C and showed that tissues regained baseline temperatures within 5 min. Before sonication, coefficient of variation for repeat ADC measurements was 0.8%. After sonication, ADC increased in the muscle adjacent to the exposed periosteum, it was maximal 1-5 min after sonication, and it significantly differed between samples with persistent versus non-persistent ADC changes beyond 20 min. ADC increases at 20 min were stable for 2 h and correlated significantly with thermal parameters (ADC versus applied acoustic energy at 16-20 min: r = 0.77, p < 0.001). A 20% ADC increase resulted in clear macroscopic tissue damage.

CONCLUSIONS

Our preliminary results suggest that DWI can detect intra-procedural changes in ex-vivo muscle overlying the periosteum. This could be useful for studying the safety and efficacy of clinical MR-guided HIFU bone treatments.

Diagnostic value of apparent diffusion coefficient in differentiating between high-grade gliomas and brain metastases

Background High-grade gliomas (HGGs) and brain metastases (BMs) can display similar imaging characteristics on conventional MRI. In HGGs, the peritumoral edema may be infiltrated by the malignant cells, which was not observed in BMs. Purpose To determine whether the apparent diffusion coefficient values could differentiate HGGs from BMs. Material and Methods Fifty-seven patients underwent conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) before treatment. The minimum and mean ADC in the enhancing tumor (ADC_min, ADC_mean) and the minimum ADC in the peritumoral region (ADC_edema) were measured from ADC maps. To determine whether there was a statistical difference between groups, ADC values were compared. A receiver operating characteristic (ROC) curve analysis was used to determine the cutoff ADC value for distinguishing between HGGs and BMs. Results The mean ADC_min values in the intratumoral regions of HGGs were significantly higher than those in BMs. No differences were observed between groups regarding ADC_mean values. The mean ADC_min values in the peritumoral edema of HGGs were significantly lower than those in BMs. According to ROC curve analysis, a cutoff value of 1.332 × 10^-3mm²/s for the ADC_edema generated the best combination of sensitivity (95%) and specificity (84%) for distinguishing between HGGs and BMs. The same value showed a sensitivity of 95.6% and a specificity of 100% for distinguishing between GBMs and BMs. Conclusion ADC values from DWI were found to distinguish between HGGs and solitary BMs. The peritumoral ADC values are better than the intratumoral ADC values in predicting the tumor type.