Diffusion weighted imaging: Technique and applications

Brain damage by trauma

Traumatic brain injury (TBI) represents a major clinical and economic challenge for health systems worldwide, and it is considered one of the leading causes of disability in young adults. The recent development of brain-computer interface (BCI) tools to target cognitive and motor impairments has led to the exploration of these techniques as potential therapeutic tools in patients with TBI. However, little evidence has been gathered so far to support applicability and efficacy of BCIs for TBI in a clinical setting. In the present chapter, results from studies using BCI approaches in conscious patients with TBI or in animal models of TBI as well as an overview of future directions in the use of BCIs to treat cognitive symptoms in this patient population will be presented.

Children with epilepsy demonstrate macro- and microstructural changes in the thalamus, putamen, and amygdala

PURPOSE

Despite evidence for macrostructural alteration in epilepsy patients later in life, little is known about the underlying pathological or compensatory mechanisms at younger ages causing these alterations. The aim of this work was to investigate the impact of pediatric epilepsy on the central nervous system, including gray matter volume, cerebral blood flow, and water diffusion, compared with neurologically normal children.

METHODS

Inter-ictal magnetic resonance imaging data was obtained from 30 children with epilepsy ages 1-16 (73% F, 27% M). An atlas-based approach was used to determine values for volume, cerebral blood flow, and apparent diffusion coefficient in the cerebral cortex, hippocampus, thalamus, caudate, putamen, globus pallidus, amygdala, and nucleus accumbens. These values were then compared with previously published values from 100 neurologically normal children using a MANCOVA analysis.

RESULTS

Most brain volumes of children with epilepsy followed a pattern similar to typically developing children, except for significantly larger putamen and amygdala. Cerebral blood flow was also comparable between the groups, except for the putamen, which demonstrated decreased blood flow in children with epilepsy. Diffusion (apparent diffusion coefficient) showed a trend towards higher values in children with epilepsy, with significantly elevated diffusion within the thalamus in children with epilepsy compared with neurologically normal children.

CONCLUSION

Children with epilepsy show statistically significant differences in volume, diffusion, and cerebral blood flow within their thalamus, putamen, and amygdala, suggesting that epilepsy is associated with structural changes of the central nervous system influencing brain development and potentially leading to poorer neurocognitive outcomes.

Elimination of residual aliasing artifact that resembles brain lesion on multi-oblique diffusion-weighted echo-planar imaging with parallel imaging using virtual coil acquisition

BACKGROUND

Single-shot diffusion-weighted echo-planar imaging (ssDW-EPI) acquired with parallel imaging and a multi-oblique scan plane may suffer from residual aliasing artifacts, resembling lesions on the calculated apparent diffusion coefficient (ADC) map.

PURPOSE

To combine ssDW-EPI and virtual coil acquisition and develop a self-reference reconstruction method to eliminate the residual aliasing artifact on multi-oblique ssDW-EPI sequence with parallel imaging and multiple signal averaging.

STUDY TYPE

Prospective.

SUBJECTS

Three healthy subjects and 50 stroke patients.

FIELD STRENGTH/SEQUENCE

Conventional ssDW-EPI with parallel imaging, and proposed ssDW-EPI with virtual coil acquisition at 1.5T.

ASSESSMENT

The efficacy of the proposed method was evaluated in 50 stroke patients by comparing the ssDW-EPI with conventional parallel imaging reconstructions. The extent of residual aliasing artifacts were rated on a 5-point Likert scale by three independent raters. Only the data without residual aliasing artifacts on conventional ssDW-EPI were included for the assessment of signal-to-noise ratio (SNR), ghost-to-signal ratio (GSR), and ADC.

STATISTICAL TESTS

The interobserver agreements for examining residual aliasing artifacts were measured by the intraclass correlation coefficient (ICC). A two-sample t-test was performed for comparing SNR, GSR, and ADC.

RESULTS

There was a perfect agreement (ICC = 1.00) in the examination of residual aliasing artifacts on images obtained using the proposed method. The incidence rates of the residual aliasing artifact on the ADC maps obtained from the scanner console and proposed method were 60% (ie, 30 out of 50) and 0%, respectively. The proposed method offers significantly lower GSR than conventional parallel imaging reconstruction (P < 0.001). There was no significant difference in SNR (P = 0.20-0.51) and ADC values (P = 0.20-0.94) between conventional parallel imaging reconstructions and the proposed method.

DATA CONCLUSION

It appears that our method could effectively eliminate artifacts and significantly improve the GSR of b = 0 T₂ WI and b > 0 DWI, as well as permit ADC measurement consistent with conventional techniques. Our method may be beneficial to clinical assessment of the brain that utilizes multi-oblique ssDW-EPI.

LEVEL OF EVIDENCE

1 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1442-1453.

In-Vivo Retention of 5-Fluorouracil Using 19F Magnetic Resonance Chemical Shift Imaging in Colorectal Cancer in a Murine Model

Colorectal cancer is the third leading cause of cancer death worldwide. 5-Fluorouracil (5-FU) is one of the most commonly used chemotherapies for treatment of solid tumours, including colorectal cancer. The efficacy of treatment is dependent on tumour type and can only be determined six weeks after beginning chemotherapy, with only 40–50% of patients responding positively to the 5-FU therapy. In this paper, we demonstrate the potential of using Magnetic Resonance (MR) Chemical Shift Imaging (CSI) for in-vivo monitoring of 5-FU tumor-retention in two different colorectal tumour types (HT-29 & H-508). Time curves for 5-FU signals from the liver and bladder were also acquired. We observed significant differences (p < 0.01) in 5-FU signal time dependencies for the HT-29 and H-508 tumours. Retention of 5-FU occurred in the H-508 tumour, whereas the HT-29 tumour is not expected to retain 5FU due to the observation of the negative b time constant indicating a decline in 5FU within the tumour. This study successfully demonstrates that CSI may be a useful tool for early identification of 5-FU responsive tumours based on observed tumour retention of the 5-FU.

Increased sensitivity to traumatic axonal injury on postconcussion diffusion tensor imaging scans in National Football League players by using premorbid baseline scans

OBJECTIVE

Statistical challenges exist when using diffusion tensor imaging (DTI) to assess traumatic axonal injury (TAI) in individual concussed athletes. The authors examined active professional American football players over a 6-year time period to study potential TAI after concussion and assess optimal methods to analyze DTI at the individual level.

METHODS

Active American professional football players recruited prospectively were assessed with DTI, conventional MRI, and standard clinical workup. Subjects underwent an optional preseason baseline scan and were asked to undergo a scan within 5 days of concussion during gameplay. DTI from 25 age- and sex-matched controls were obtained. Both semiautomated region-of-interest analysis and fully automated tract-based spatial statistics (TBSS) were used to examine DTI at individual and group levels. Statistical differences were assessed comparing individual DTI data to baseline imaging versus a normative database. Group-level comparisons were also performed to determine if longer exposure to professional-level play or prior concussion cause white matter microstructural integrity changes.

RESULTS

Forty-nine active professional football players were recruited into the study. Of the 49 players, 7 were assessed at baseline during the preseason and after acute concussion. An additional 18 players were assessed after acute concussion only. An additional 24 players had only preseason baseline assessments. The results suggest DTI is more sensitive to suspected TAI than conventional MRI, given that 4 players demonstrated decreased fractional anisotropy (FA) in multiple tracts despite normal conventional MRI. Furthermore, the data suggest individual assessment of DTI data using baseline premorbid imaging is more sensitive than typical methods of comparing data to a normative control group. Among all subjects with baseline data, 1 reduced FA tract (± 2.5 standard deviations) was found using the typical normative database reference versus 10 statistically significant (p < 0.05) reduced FA tracts when referencing internal control baseline data. All group-level comparisons were statistically insignificant (p > 0.05).

CONCLUSIONS

Baseline premorbid DTI data for individual DTI analysis provides increased statistical sensitivity. Specificity using baseline imaging also increases because numerous potential etiologies for reduced FA may exist prior to a concussion. These data suggest that there is a high potential for false-positive and false-negative assessment of DTI data using typical methods of comparing an individual to normative groups given the variability of FA values in the normal population.

Diffusion-Weighted Magnetic Resonance Imaging for Early Detection of Chemotherapy Resistance in Non-Small Cell Lung Cancer

Background

The aim of this study was to examine the role of magnetic resonance imaging-diffusion weighted imaging (MRI-DWI) in the early detection of chemotherapy resistance in non-small cell lung cancer (NSCLC) patients.

Material/Methods

MRI-DWI and computed tomography (CT) were carried out in 75 patients with newly diagnostic NSCLC before and after first, second, fourth, and sixth cycles of chemotherapy. Resistance to chemotherapy was assessed based on the change in the largest tumor diameter after chemotherapy. Diffusion of water molecule in each lesion was quantitatively measured by apparent diffusion coefficient (ADC). The diagnostic results of DWI after first and second cycle of chemotherapy were analyzed by the area under receiver operating characteristics curve (ROC).

Results

Among the patients, 43 patients were chemo-resistance while 32 patients were chemo-sensitive. The ADC changing rate between second and first cycle of chemotherapy was significantly higher in chemo-sensitive patients compared with chemo-resistance patients (t=3.236, P=0.002). The ROC showed cutoff values of the ADC changing rate after first and second cycles of chemotherapy for resistance/sensitive discrimination were 23.6% and 5.56%, respectively. DWI after first and second cycles of therapy showed sensitivities of 55.8% and 55.8%, specificities of 65.6% and 87.5%, and area under ROC of 0.568 and 0.733, respectively.

Conclusions

ADC changing rate between first and second cycles of chemotherapy could sensitively distinguish chemo-sensitive and chemo-resistant tumors at earlier stages, which may direct treatment adjustment and improve the prognosis of patients.

The Influence of Bowel Preparation on ADC Measurements: Comparison between Conventional DWI and DWIBS Sequences

Background and objectives: The aim of the study was to assess whether there were differences between apparent diffusion coefficient (ADC) values of diffusion-weighted imaging (DWI) and diffusion-weighted imaging with background body signal suppression (DWIBS) sequences in non-prepared and prepared bowels before and after preparation with an enteric hyperosmolar agent, to assess whether ADC measurements have the potential to avoid bowel preparation and whether ADC-DWIBS has advantages over ADC-DWI. Materials and Methods: 106 adult patients without evidence of inflammatory bowel disease (IBD) underwent magnetic resonance (MR) enterography before and after bowel preparation. ADC-DWI and ADC-DWIBS values were measured in the intestinal and colonic walls demonstrating high signal intensity (SI) at DWI tracking images of b = 800 s/mm² before and after preparation. Results: There were significant difference (p < 0.0001) in both ADC-DWI and ADC-DWIBS results between non-prepared and prepared jejunum for DWI being 1.09 × 10⁻³ mm²/s and 1.76 × 10⁻³ mm²/s, respectively, and for DWIBS being 0.91 × 10⁻³ mm²/s and 1.75 × 10⁻³ mm²/s, respectively. Both ADC-DWI and DWIBS also showed significant difference between non-prepared and prepared colon (p < 0.0001), with DWI values 1.41 × 10⁻³ mm²/s and 2.13 × 10⁻³ mm²/s, and DWIBS—1.01 × 10⁻³ mm²/s and 2.04 × 10⁻³ mm²/s, respectively. No significant difference between ADC-DWI and ADC-DWIBS was found in prepared jejunum (p = 0.84) and prepared colon (p = 0.58), whereas a significant difference was found in non-prepared jejunum and non-prepared colon (p = 0.0001 in both samples). Conclusions: ADC between DWI and DWIBS does not differ in prepared bowel walls but demonstrates a difference in non-prepared bowel. ADC in non-prepared bowel is lower than in prepared bowel and possible overlap with the ADC range of IBD is possible in non-prepared bowel. ADC-DWIBS has no advantage over ADC-DWI in regard to IBD assessment.

The usefulness of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) sequences visual assessment in the early diagnosis of axial spondyloarthritis

The aim of the study was to compare the diagnostic efficacy of the visual assessment of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) sequences compared to the STIR sequence in the diagnostics of active sacroiliitis in the course of axial spondyloarthritis (axSpA). The study group consisted of 49 patients who had undergone multiparametric magnetic resonance imaging of the sacroiliac joints (SIJs) due to clinical suspicion of axSpA. Two independent observers retrospectively assessed four quadrants of the SIJs for the presence of subchondral bone marrow oedema/osteitis with the use of modified SPARCC score in sequences: STIR, DWI (with ADC map) and DCE. Diagnostic efficiency parameters were calculated for DWI and DCE sequence separately, using STIR sequence as a reference. Inter-observer agreement was evaluated with the use of κ coefficient. Patients' clinical symptoms were analysed to identify the group fulfilling the imaging arm of the ASAS criteria for axSpA. Overall, 46.9% (n = 23) of patients fulfilled the imaging arm of ASAS criteria for axial spondyloarthritis. DWI with ADC map: accuracy 95.6%, sensitivity 99.4%, specificity 54.0%. DCE sequence: accuracy 96.8%, sensitivity 98.4%, specificity 79.5%. The highest level of inter-observer agreement was achieved for STIR sequence (κ = 0.888), slightly lower for DCE sequence (κ = 0.773) and the lowest for DWI with ADC (κ = 0.674). Visual assessment of the DWI and DCE sequences has high accuracy and sensitivity of bone marrow oedema/osteitis detection, but the specificity and inter-observer agreement are poor, especially for the DWI sequence with ADC maps.

Diffusion-weighted imaging (DWI) highlights SDHB-related tumours: A pilot study

OBJECTIVE

There is consensus that asymptomatic carriers of SDHB mutations should undergo periodic surveillance imaging. MRI has the advantage of avoiding radiation exposure but its sensitivity and specificity for detecting phaeochromocytoma and paraganglioma (PPGL) are dependent on sequences performed and expertise of reporting radiologists. We aim to highlight the additional value of diffusion-weighted imaging (DWI) for MR based surveillance, demonstrating DWI's ability to identify small PPGLs at all body sites.

DESIGN

We presented DWI sequences taken as part of SDHB surveillance to a radiologist, expert in reporting PPGL screening scans. Areas of high signal on DWI were interrogated using other standard MRI sequences.

PATIENTS

We reviewed the MRI scans for 18 SDHB mutation carriers with a total of 18 histologically proven SDHB-related tumours and 12 presumed PGLs/metastatic deposits.

RESULTS

The DWI sequences identified all 30 lesions. False-positive lesions were excluded by standard sequences. The tumours detected by DWI ranged in size from 5 to 52 mm. PPGLs were identified on DWI in the abdomen (n = 14), adrenal gland (n = 1), thorax (n = 3), neck (n = 2) and bladder (n = 2). Additionally, other SDHB-related tumours (GIST, RCC) were also highlighted by DWI, as were metastatic deposits in the liver and bone.

CONCLUSIONS

These preliminary data suggest that DWI has high sensitivity and can identify even small SDHB-related tumours. If these findings are confirmed in larger series, for all SDH subunits, it will provide reassurance about identifying small SDH-related tumours, without exposing patients to the consequences of radiation-based imaging and will secure the role of MRI for surveillance imaging.

A Simplified Crossing Fiber Model in Diffusion Weighted Imaging

Diffusion MRI (dMRI) is a vital source of imaging data for identifying anatomical connections in the living human brain that form the substrate for information transfer between brain regions. dMRI can thus play a central role toward our understanding of brain function. The quantitative modeling and analysis of dMRI data deduces the features of neural fibers at the voxel level, such as direction and density. The modeling methods that have been developed range from deterministic to probabilistic approaches. Currently, the Ball-and-Stick model serves as a widely implemented probabilistic approach in the tractography toolbox of the popular FSL software package and FreeSurfer/TRACULA software package. However, estimation of the features of neural fibers is complex under the scenario of two crossing neural fibers, which occurs in a sizeable proportion of voxels within the brain. A Bayesian non-linear regression is adopted, comprised of a mixture of multiple non-linear components. Such models can pose a difficult statistical estimation problem computationally. To make the approach of Ball-and-Stick model more feasible and accurate, we propose a simplified version of Ball-and-Stick model that reduces parameter space dimensionality. This simplified model is vastly more efficient in the terms of computation time required in estimating parameters pertaining to two crossing neural fibers through Bayesian simulation approaches. Moreover, the performance of this new model is comparable or better in terms of bias and estimation variance as compared to existing models.

Image quality and diagnostic accuracy of complex-averaged high b value images in diffusion-weighted MRI of prostate cancer

PURPOSE

To evaluate the impact of complex-averaging on image quality (IQ) and diagnostic accuracy of acquired and calculated high b value (aHBV, cHBV) images in diffusion-weighted prostate MRI.

MATERIALS AND METHODS

This retrospective study included 84 patients who underwent multiparametric prostate MRI at 3 Tesla without endorectal coil. DWIs were acquired at three different b values which included two lower b values (b = 50,900 s/mm²) and one higher b value (aHBV at 2000 s/mm²). The acquired data were postprocessed to generate two different types of trace-weighted images-using conventional magnitude-averaging and complex-averaging. Using lower b values (b = 50,900 s/mm²) from both conventional and complex-averaged image sets, cHBV images (b = 2000 s/mm²) and ADC maps were derived. All image sets were reviewed by two radiologists in different reading sessions to assess image quality and PIRADS. The diagnostic accuracy of different image sets for the detection of prostate lesions was performed by correlating PIRADS and Gleason scores.

RESULTS

Complex-averaging did not impact ADC values of the prostate lesions compared to magnitude-averaging (P = 0.08). Complex-averaging improved image quality of acquired high b value and calculated high b value images (P < 0.0001). Complex-averaging also improved the level of confidence (LOC) of the acquired high b value for both readers (P < 0.0001, P < 0.05), but only for reader A in calculated high b value (P < 0.0001). The image quality of calculated high b value images was not significantly different than acquired high b value images. The dataset combining complex-averaging and calculated high b value provided the highest diagnostic accuracy (but not statistically significant) for detection of the significant prostate lesion compared to the magnitude-averaged acquired high b value (79.55% vs. 72.73%; P = 0.317). The mean acquisition time for b = 2000 s/mm² sequence (aHBV) was 6 min 30 s (± 1 min 16 s) out of a total of 28 min 31 s (± 4 min 26 s) for the entire mp-MRI protocol (approximately 25% of total scan time).

CONCLUSION

Complex-averaging provides better image quality and level of confidence without significant impact on ADC values and diagnostic accuracy for detection of the significant prostate lesions . The calculated high b value images are also comparable to (and can substitute) the acquired high b value images which can help in reducing the imaging time.

Profile of children with cerebral palsy spectrum disorder and a normal MRI study

OBJECTIVE

This study looks at what profile can be expected in children with cerebral palsy spectrum disorder (CP) and a normal MRI.

METHODS

The data were excerpted from the Canadian Cerebral Palsy Registry database. Only patients who had undergone MRI were included in the analysis. Neuroimaging classification was ascertained by university-based pediatric neuroradiologists and split into 2 categories: normal and abnormal MRIs. Six factors were then compared between those 2 groups: prematurity, perinatal adversity, presence of more than 1 comorbidity, CP subtype, bimanual dexterity (Manual Ability Classification System [MACS]), and gross motor function (Gross Motor Function Classification System [GMFCS]).

RESULTS

Participants with no perinatal adversity were 5.518 times more likely to have a normal MRI (p < 0.0001, 95% confidence interval [CI] 4.153-7.330). Furthermore, participants with dyskinetic, ataxic/hypotonic, and spastic diplegic forms of CP were 2.045 times more likely to have a normal MRI than those with hemiplegia, triplegia, and quadriplegia (p < 0.0001, 95% CI 1.506-2.778). No significant difference was found in prematurity, GMFCS levels, MACS levels, and the number of comorbidities.

CONCLUSIONS

Normal MRIs were associated with lack of perinatal adversity as well as with the dyskinetic, ataxic/hypotonic, and spastic diplegic CP subtypes. As MRI normality is not strongly associated with the severity of CP, continuous follow-up in children with normal imaging appears warranted. Further advanced imaging modalities, as well as strong consideration for metabolic and genetic testing, may provide additional insights into causal pathways in this population.

High-field mr diffusion-weighted image denoising using a joint denoising convolutional neural network

BACKGROUND

Low signal-to-noise ratio (SNR) has been a major limiting factor for the application of higher-resolution diffusion-weighted imaging (DWI). Most of the conventional denoising models suffer from the drawbacks of shallow feature extraction and hand-crafted parameter tuning. Although multiple studies have shown the promising applications of image denoising using convolutional neural networks (CNNs), none of them have considered denoising multiple b-value DWIs using a multichannel CNN model.

PURPOSE

To present a joint denoising CNN (JD-CNN) model to improve the SNR of multiple b-value DWI.

STUDY TYPE

Retrospective technical development.

POPULATION

Twenty healthy rats and two rats with clinically confirmed focal cortical dysplasia were included to evaluate the performance of the proposed method.

FIELD STRENGTH/SEQUENCE

11.7T MRI, a multiple b-values DWI sequence.

ASSESSMENT

The total variation (TV) and BM3D denoising methods were also performed on the same dataset for comparison. Peak SNR (PSNR) and normalized mean square error (NMSE) were calculated for the assessment of image qualities.

STATISTICAL TESTS

A paired Student's t-test was conducted to compare the diffusion parameter measurements between different approaches. P < 0.01 was considered statistically significant.

RESULTS

Simulation results showed substantial improvement of image quality after JD-CNN denoising (PSNR of original image: 23.15 ± 1.77; PSNR of denoised image: 42.94 ± 2.12). The proposed method outperforms the state-of-the-art methods on high b-value DWIs in terms of PSNR (TV: 33.51 ± 0.83, BM3D: 35.12 ± 0.94, JD-CNN: 46.52 ± 0.98). In addition, the NMSE of the estimated apparent diffusion coefficient (ADC) reduces from 0.72 ± 0.13 to 0.45 ± 0.06 (P < 0.01) with the application of the JD-CNN model.

DATA CONCLUSION

The proposed method is able to remove noise with a wide range of noise levels in multiple b-value DWI and improve the diffusion parameter estimation. This shows potential clinical promise.

LEVEL OF EVIDENCE

2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:1937-1947.

Renal Allograft Rejection: Noninvasive Ultrasound- and MRI-Based Diagnostics

To date, allogeneic kidney transplantation remains the best available therapeutic option for patients with end-stage renal disease regarding overall survival and quality of life. Despite the advancements in immunosuppressive drugs and protocols, episodes of acute allograft rejection, a sterile inflammatory process, continue to endanger allograft survival. Since effective treatment for acute rejection episodes is available, instant diagnosis of this potentially reversible graft injury is imperative. Although histological examination by invasive core needle biopsy of the graft remains the gold standard for the diagnosis of ongoing rejection, it is always associated with the risk of causing substantial graft injury as a result of the biopsy procedure itself. At the same time, biopsies are not immediately feasible for a considerable number of patients taking anticoagulants due to the high risk of complications such as bleeding and uneven distribution of pathological changes within the graft. This can result in the wrong diagnosis due to the small size of the tissue sample taken. Therefore, there is a need for a tool that overcomes these problems by being noninvasive and capable of assessing the whole organ at the same time for specific and fast detection of acute allograft rejection. In this article, we review current state-of-the-art approaches for noninvasive diagnostics of acute renal transplant inflammation, i.e., rejection. We especially focus on nonradiation-based methods using magnetic resonance imaging (MRI) and ultrasound.

Assessment of the extracellular volume fraction for the grading of clear cell renal cell carcinoma: first results and histopathological findings

OBJECTIVES

To assess the potential of T1 mapping-based extracellular volume fraction (ECV) for the identification of higher grade clear cell renal cell carcinoma (cRCC), based on histopathology as the reference standard.

METHODS

For this single-center, institutional review board-approved prospective study, 27 patients (17 men, median age 62 ± 12.4 years) with pathologic diagnosis of cRCC (nucleolar International Society of Urological Pathology (ISUP) grading) received abdominal MRI scans at 1.5 T using a modified Look-Locker inversion recovery (MOLLI) sequence between January 2017 and June 2018. Quantitative T1 values were measured at different time points (pre- and postcontrast agent administration) and quantification of the ECV was performed on MRI and histological sections (H&E staining).

RESULTS

Reduction in T1 value after contrast agent administration and MR-derived ECV were reliable predictors for differentiating higher from lower grade cRCC. Postcontrast T1_diff values (T1_diff = T1 difference between the native and nephrogenic phase) and MR-derived ECV were significantly higher for higher grade cRCC (ISUP grades 3-4) compared with lower grade cRCC (ISUP grades 1-2) (p < 0.001). A cutoff value of 700 ms could distinguish higher grade from lower grade tumors with 100% (95% CI 0.69-1.00) sensitivity and 82% (95% CI 0.57-0.96) specificity. There was a positive and strong correlation between MR-derived ECV and histological ECV (p < 0.01, r = 0.88). Interobserver agreement for quantitative longitudinal relaxation times in the T1 maps was excellent.

CONCLUSIONS

T1 mapping with ECV measurement could represent a novel in vivo biomarker for the classification of cRCC regarding their nucleolar grade, providing incremental diagnostic value as a quantitative MR marker.

KEY POINTS

• Reduction in MRI T1 relaxation times after contrast agent administration and MR-derived extracellular volume fraction are useful parameters for grading of clear cell renal cell carcinoma (cRCC). • T1 differences between the native and the nephrogenic phase are higher for higher grade cRCC compared with lower grade cRCC and MRI-derived extracellular volume fraction (ECV) and histological ECV show a strong correlation. • T1 mapping with ECV measurement may be helpful for the noninvasive assessment of cRCC pathology, being a safe and feasible method, and it has potential to optimize individualized treatment options, e.g., in the decision of active surveillance.

Differentiation between malignant and benign musculoskeletal tumors using diffusion kurtosis imaging

OBJECTIVE

The purpose of this study was to evaluate differences in parameters of diffusion kurtosis imaging (DKI) and minimum apparent diffusion coefficient (ADC_min) between benign and malignant musculoskeletal tumors.

MATERIALS AND METHODS

In this prospective study, 43 patients were scanned using a DKI protocol on a 3-T MR scanner. Eligibility criteria were: non-fatty, non-cystic soft tissue or osteolytic tumors; > 2 cm; location in the retroperitoneum, pelvis, leg, or neck; and no prior treatment. They were clinically or histologically diagnosed as benign (n = 27) or malignant (n = 16). In the DKI protocol, diffusion-weighted imaging was performed using four b values (0-2000 s/mm²) and 21 diffusion directions. Mean kurtosis (MK) values were calculated on the MR console. A recently developed software application enabling reliable calculation was used for DKI analysis.

RESULTS

MK showed a strong correction with ADC_min (Spearman's rs = 0.95). Both MK and ADC_min values differed between benign and malignant tumors (p < 0.01). For benign and malignant tumors, the mean MK values (± SD) were 0.49 ± 0.17 and 1.14 ± 0.30, respectively, and ADC_min values were 1.54 ± 0.47 and 0.49 ± 0.17 × 10^-3 mm²/s, respectively. At cutoffs of MK = 0.81 and ADC_min = 0.77 × 10^-3 mm²/s, the specificity and sensitivity for diagnosis of malignant tumors were 96.3 and 93.8% for MK and 96.3 and 93.8% for ADC_min, respectively. The areas under the curve were 0.97 and 0.99 for MK and ADC_min, respectively (p = 0.31).

CONCLUSIONS

MK and ADC_min showed high diagnostic accuracy and strong correlation, reflecting the accuracy of MK. However, no clear added value of DKI could be demonstrated in differentiating musculoskeletal tumors.

Vital Sign Monitoring and Cardiac Triggering at 1.5 Tesla: A Practical Solution by an MR-Ballistocardiography Fiber-Optic Sensor

This article presents a solution for continuous monitoring of both respiratory rate (RR) and heart rate (HR) inside Magnetic Resonance Imaging (MRI) environments by a novel ballistocardiography (BCG) fiber-optic sensor. We designed and created a sensor based on the Fiber Bragg Grating (FBG) probe encapsulated inside fiberglass (fiberglass is a composite material made up of glass fiber, fabric, and cured synthetic resin). Due to this, the encapsulation sensor is characterized by very small dimensions (30 × 10 × 0.8 mm) and low weight (2 g). We present original results of real MRI measurements (conventionally most used 1.5 T MR scanner) involving ten volunteers (six men and four women) by performing conventional electrocardiography (ECG) to measure the HR and using a Pneumatic Respiratory Transducer (PRT) for RR monitoring. The acquired sensor data were compared against real measurements using the objective Bland⁻Altman method, and the functionality of the sensor was validated (95.36% of the sensed values were within the ±1.96 SD range for the RR determination and 95.13% of the values were within the ±1.96 SD range for the HR determination) by this means. The accuracy of this sensor was further characterized by a relative error below 5% (4.64% for RR and 4.87% for HR measurements). The tests carried out in an MRI environment demonstrated that the presence of the FBG sensor in the MRI scanner does not affect the quality of this imaging modality. The results also confirmed the possibility of using the sensor for cardiac triggering at 1.5 T (for synchronization and gating of cardiovascular magnetic resonance) and for cardiac triggering when a Diffusion Weighted Imaging (DWI) is used.

Differentiation between benign and malignant thyroid nodules using diffusion-weighted imaging, a 3-T MRI study

Background:

Preoperative differentiation of benign from malignant thyroid nodules remains a challenge. Aims: This study assessed the accuracy of diffusion-weighted imaging (DWI) for differentiation between benign and malignant thyroid nodules.

Materials and Methods:

Preoperative DWI was performed in patients with thyroid nodule by means of a 3-T scanner magnetic resonance imaging (MRI). Images were obtained at b value of 50, 500, and 1000 mm²/s to draw an ADC (apparent diffusion coefficient) map. Findings were compared with postoperative histopathologic results. Receiver operating characteristic curve was used to assess the accuracy of different cutoff points.

Results:

Forty-one thyroid nodules (26 benign and 15 malignant) were included in this study. None of static MRI parameters such as signal intensity, heterogeneity, and nodule border was useful to discriminate between benign and malignant lesions. Mean ADC value was (1.94 ± 0.54) × 10^-3 mm²/s and (0.89 ± 0.29) × 10^-3 mm²/s in benign and malignant nodules, respectively (P-value < 0.005). ADC value cutoff of 1 × 10^-3 mm²/s yielded an accuracy, sensitivity, and specificity of 93%, 87%, and 96% to discriminate benign and malignant nodules.

Conclusion:

DWI is highly accurate for discrimination between benign and malignant thyroid nodules.

Esophageal carcinoma: Intravoxel incoherent motion diffusion-weighted MRI parameters and histopathological correlations

BACKGROUND

The pathological grade of esophageal carcinoma is highly determinant of patient prognosis, but it still cannot be adequately evaluated preoperatively. Compared with conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) diffusion-weighted MRI can separate true molecular diffusion and perfusion in tissues and has been shown to be useful in characterizing malignant tumors. There is no report that compared IVIM and conventional DWI in grading esophageal carcinoma.

PURPOSE

To prospectively determine the diagnostic performance of conventional DWI and IVIM models in differentiating the pathological differentiated grade of esophageal carcinoma.

STUDY TYPE

Prospective.

POPULATION

A cohort comprising 81 patients with newly diagnosed esophageal squamous cell carcinoma (ESCC) between December 2015 and August 2017 were evaluated.

FIELD STRENGTH/SEQUENCE

3.0T, axial echo-planer imaging, fast spin echo (FSE) sequence, IVIM sequence (b = 0, 20, 50, 80, 100, 150, 200, 400, 600, 800, 1000, 1200).

ASSESSMENT

Apparent diffusion coefficient (ADC), true ADC (ADC_slow ), pseudo ADC (ADC_fast ), and perfusion fraction (f) of each tumor were calculated by two independent radiologists. Histopathologic grade was used as the reference standard.

STATISTICAL TESTS

Games-Howell test; diagnostic accuracy; Spearman correlation; intraclass correlation coefficient; and Bland-Altman analysis. Receiver operating characteristics (ROC) curves.

RESULTS

ADC_slow demonstrated the highest area under curve (AUC) with a value of 0.830 (95% confidence interval [CI]: 0.730-0.904) and 0.816 (95% CI: 0.714-0.893) by two radiologists, followed by ADC with a value of 0.754 (95% CI: 0.646-0.843) and 0.761 (95% CI: 0.653-0.848). Good correlation was obtained between the histologic grade and ADC_slow (r_(R1)  = 0.748, r_(R2)  = 0.720) and ADC (r_(R1)  = 0.576, r_(R2)  = 0.571).

DATA CONCLUSION

ADC_slow and ADC had a significantly higher performance than the ADC_fast and f, and ADC_slow had a significantly higher performance than the ADC.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:253-261.

Apparent diffusion coefficient reproducibility in brain tumors measured on 1.5 and 3 T clinical scanners: A pilot study

BACKGROUND

Gradient and coil systems, pulse sequence design, and imaging parameters, as well as different scanners, can influence apparent diffusion coefficient (ADC) values. The aim of this study was to evaluate the effect of two different field strengths on the reproducibility of mean absolute ADC measurements in various primary and secondary brain tumors.

METHODS

Fifty patients with histologically proven brain tumors were prospectively examined on two MR scanners from the same vendor, with different field strengths-1.5T and 3T-on the same day. Absolute ADC values were compared using the Wilcoxon matched-pairs signed-rank test. Inter-scanner agreement between two different fields in the same tumor was examined using correlation coefficients, and the discrepancy between the highest and the lowest mean absolute ADC values between scanners was tested using a one-way analysis of variance. Statistical significance was set at p < 0.05.

RESULTS

There was no statistically significant difference between mean absolute ADC values obtained on 1.5T and 3T scanners for all patients and all brain tumor types. The intratumoral difference in ADC values, averaged from two scanners in the same tumor type, ranged from 1.58 to 4.5% for 1.5T, and from 1.18 to 4.37% for 3T.Inter-scanner agreement was high, and the kappa coefficient ranged from 0.88 to 0.99, with no significant difference between obtained values on different field strengths.

CONCLUSION

Based on the results obtained in our study, there is no significant difference between mean absolute ADC values measured in various primary and secondary brain tumors at different field strengths (1.5 and 3.0T MR systems), in the same patient, and in the same tumor, measured on the same day.

A review of magnetic resonance enterography-based indices for quantification of Crohn's disease inflammation

Magnetic resonance enterography (MRE) is a leading radiological modality in Crohn's disease (CD) and is used together with laboratory findings and endoscopic examinations for the evaluation of patients during initial diagnosis and follow up. Over the years, there has been great progress in the understanding of CD and there is a continuous strive to achieve better monitoring of patients and to develop new modalities which will predict disease course and thus help in clinical decisions making. An objective evaluation of CD using a quantification score is not a new concept and there are different clinical, endoscopies, radiological and combined indices which are used in clinical practice. Such scores are a necessity in clinical trials on CD for evaluation of disease response, however, there is no consensus of the preferred MRE score and they are not routinely used. This review presents MRE-based indices in use in the last decade: the Magnetic Resonance Index of Activity (MaRIA), the Clermont score, the Crohn's Disease Magnetic Resonance Imaging (MRI) Index (CDMI), the Magnetic Resonance Enterography Global Score (MEGS) and the Lemann index. We compare the different indices and evaluate the clinical research that utilized them. The aim of this review is to provide a reference guide for researchers and clinicians who incorporate MRE indices in their work. When devising future indices, accumulated data of the existing indices must be taken into account, as each of the current indices has its own strengths and weakness.

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

AIM

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

METHODS

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

RESULTS

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

CONCLUSION

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

Brain metastases: neuroimaging

Magnetic resonance imaging (MRI) is the cornerstone for evaluating patients with brain masses such as primary and metastatic tumors. Important challenges in effectively detecting and diagnosing brain metastases and in accurately characterizing their subsequent response to treatment remain. These difficulties include discriminating metastases from potential mimics such as primary brain tumors and infection, detecting small metastases, and differentiating treatment response from tumor recurrence and progression. Optimal patient management could be benefited by improved and well-validated prognostic and predictive imaging markers, as well as early response markers to identify successful treatment prior to changes in tumor size. To address these fundamental needs, newer MRI techniques including diffusion and perfusion imaging, MR spectroscopy, and positron emission tomography (PET) tracers beyond traditionally used 18-fluorodeoxyglucose are the subject of extensive ongoing investigations, with several promising avenues of added value already identified. These newer techniques provide a wealth of physiologic and metabolic information that may supplement standard MR evaluation, by providing the ability to monitor and characterize cellularity, angiogenesis, perfusion, pH, hypoxia, metabolite concentrations, and other critical features of malignancy. This chapter reviews standard and advanced imaging of brain metastases provided by computed tomography, MRI, and amino acid PET, focusing on potential biomarkers that can serve as problem-solving tools in the clinical management of patients with brain metastases.

Inter- and intra-observer reproducibility of ADC measurements in esophageal carcinoma primary tumors

The apparent diffuse coefficient (ADC) may correlate with the treatment response to chemotherapy/radiotherapy in solid tumors. Our aim was to determine the inter- and intra-observer reproducibility of ADC measurements in primary esophageal squamous cell carcinoma (ESCC). ADCs were blindly measured in 31 patients diagnosed with ESCC by two observers before treatment (pre-ADC) and after 5^th fraction radiotherapy (intra-ADC) twice with a 2-week interval. The mean pre-ADC of primary tumors was 1.25±0.22 and 1.27±0.23 (in 10⁻³mm²/s) from observer A for measurements 1 and 2, respectively, and the intra-observer measurements were -0.02 bias vs. -0.13-0.09 limits of agreement. From observer B, the mean pre-ADC varied between 1.25±0.23 and 1.27±0.23 (in 10⁻³mm²/s) for measurements 1 and 2, respectively, and intra-observer measurements were -0.02 bias vs. -0.17∼0.16 limits of agreement. The mean pre-ADC of primary tumors was 1.26±0.24 (in 10⁻³mm²/s) from observers A and B, and inter-observer measurements were 0.01 bias vs. -0.09-0.09 limits of agreement, revealing a low inter-observer variance. Similar measurements of the intra-SD parameters showed that the pre- and intra-ADC of primary tumors differed significantly. Thus ADC measurements may have sufficient inter-observer and intra-observer reproducibility to measure primary tumor responses to treatment, and the ADCs before and during treatment differed.

Diffusion weighted magnetic resonance imaging of liver: Principles, clinical applications and recent updates

Diffusion-weighted imaging (DWI), a functional imaging technique exploiting the Brownian motion of water molecules, is increasingly shown to have value in various oncological and non-oncological applications. Factors such as the ease of acquisition and ability to obtain functional information in the absence of intravenous contrast, especially in patients with abnormal renal function, have contributed to the growing interest in exploring clinical applications of DWI. In the liver, DWI demonstrates a gamut of clinical applications ranging from detecting focal liver lesions to monitoring response in patients undergoing serial follow-up after loco-regional and systemic therapies. DWI is also being applied in the evaluation of diffuse liver diseases such as non-alcoholic fatty liver disease, hepatic fibrosis and cirrhosis. In this review, we intend to review the basic principles, technique, current clinical applications and future trends of DW-MRI in the liver.

MRI in Glioma Immunotherapy: Evidence, Pitfalls, and Perspectives

Pseudophenomena, that is, imaging alterations due to therapy rather than tumor evolution, have an important impact on the management of glioma patients and the results of clinical trials. RANO (response assessment in neurooncology) criteria, including conventional MRI (cMRI), addressed the issues of pseudoprogression after radiotherapy and concomitant chemotherapy and pseudoresponse during antiangiogenic therapy of glioblastomas (GBM) and other gliomas. The development of cancer immunotherapy forced the identification of further relevant response criteria, summarized by the iRANO working group in 2015. In spite of this, the unequivocal definition of glioma progression by cMRI remains difficult particularly in the setting of immunotherapy approaches provided by checkpoint inhibitors and dendritic cells. Advanced MRI (aMRI) may in principle address this unmet clinical need. Here, we discuss the potential contribution of different aMRI techniques and their indications and pitfalls in relation to biological and imaging features of glioma and immune system interactions.