Preoperative staging of ovarian cancer: comparison between ultrasound, CT and whole-body diffusion-weighted MRI (ISAAC study)

OBJECTIVES

To compare the performance of transvaginal and transabdominal ultrasound with that of the first-line staging method (contrast-enhanced computed tomography (CT)) and a novel technique, whole-body magnetic resonance imaging with diffusion-weighted sequence (WB-DWI/MRI), in the assessment of peritoneal involvement (carcinomatosis), lymph-node staging and prediction of non-resectability in patients with suspected ovarian cancer.

METHODS

Between March 2016 and October 2017, all consecutive patients with suspicion of ovarian cancer and surgery planned at a gynecological oncology center underwent preoperative staging and prediction of non-resectability with ultrasound, CT and WB-DWI/MRI. The evaluation followed a single, predefined protocol, assessing peritoneal spread at 19 sites and lymph-node metastasis at eight sites. The prediction of non-resectability was based on abdominal markers. Findings were compared to the reference standard (surgical findings and outcome and histopathological evaluation).

RESULTS

Sixty-seven patients with confirmed ovarian cancer were analyzed. Among them, 51 (76%) had advanced-stage and 16 (24%) had early-stage ovarian cancer. Diagnostic laparoscopy only was performed in 16% (11/67) of the cases and laparotomy in 84% (56/67), with no residual disease at the end of surgery in 68% (38/56), residual disease ≤ 1 cm in 16% (9/56) and residual disease > 1 cm in 16% (9/56). Ultrasound and WB-DWI/MRI performed better than did CT in the assessment of overall peritoneal carcinomatosis (area under the receiver-operating-characteristics curve (AUC), 0.87, 0.86 and 0.77, respectively). Ultrasound was not inferior to CT (P = 0.002). For assessment of retroperitoneal lymph-node staging (AUC, 0.72-0.76) and prediction of non-resectability in the abdomen (AUC, 0.74-0.80), all three methods performed similarly. In general, ultrasound had higher or identical specificity to WB-DWI/MRI and CT at each of the 19 peritoneal sites evaluated, but lower or equal sensitivity in the abdomen. Compared with WB-DWI/MRI and CT, transvaginal ultrasound had higher accuracy (94% vs 91% and 85%, respectively) and sensitivity (94% vs 91% and 89%, respectively) in the detection of carcinomatosis in the pelvis. Better accuracy and sensitivity of ultrasound (93% and 100%) than WB-DWI/MRI (83% and 75%) and CT (84% and 88%) in the evaluation of deep rectosigmoid wall infiltration, in particular, supports the potential role of ultrasound in planning rectosigmoid resection. In contrast, for the bowel serosal and mesenterial assessment, abdominal ultrasound had the lowest accuracy (70%, 78% and 79%, respectively) and sensitivity (42%, 65% and 65%, respectively).

CONCLUSIONS

This is the first prospective study to document that, in experienced hands, ultrasound may be an alternative to WB-DWI/MRI and CT in ovarian cancer staging, including peritoneal and lymph-node evaluation and prediction of non-resectability based on abdominal markers of non-resectability. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

Texture Analysis in the Assessment of Rectal Cancer: Comparison of T2WI and Diffusion-Weighted Imaging

Texture analysis (TA) techniques derived from T2-weighted imaging (T2WI) and apparent diffusion coefficient (ADC) maps of rectal cancer can both achieve good diagnosis performance. This study was to compare TA from T2WI and ADC maps between different pathological T and N stages to confirm which TA analysis is better in diagnosis performance. 146 patients were enrolled in this study. Tumor TA was performed on every patient's T2WI and ADC maps, respectively; then, skewness, kurtosis, uniformity, entropy, energy, inertia, and correlation were calculated. Our results demonstrated that those significant different parameters derived from T2WI had better diagnostic performance than those from ADC maps in differentiating pT3b-4 and pN1-2 stage tumors. In particular, the energy derived from T2WI was an optimal parameter for diagnostic efficiency. High-resolution T2WI plays a key point in the local stage of rectal cancer; thus, TA derived from T2WI may be a more useful tool to aid radiologists and surgeons in selecting treatment.

Correlations between DW-MRI and 18 F-FDG PET/CT parameters in head and neck squamous cell carcinoma following definitive chemo-radiotherapy

BACKGROUND

Posttreatment diffusion-weighted magnetic resonance imaging (DW-MRI) and 18F-fluorodeoxygluocose (18 F-FDG) positron emission tomography (PET) with computed tomography (PET/CT) have potential prognostic value following chemo-radiotherapy (CRT) for head and neck squamous cell carcinoma (HNSCC). Correlations between these PET/CT (standardized uptake value or SUV) and DW-MRI (apparent diffusion coefficient or ADC) parameters have only been previously explored in the pretreatment setting.

AIM

To evaluate stage III and IV HNSCC at 12-weeks post-CRT for the correlation between SUVmax and ADC values and their interval changes from pretreatment imaging.

METHODS

Fifty-six patients (45 male, 11 female, mean age 59.9 + - 7.38) with stage 3 and 4 HNSCC patients underwent 12-week posttreatment DW-MRI and 18 F-FDG PET/CT studies in this prospective study. There were 41/56 patients in the cohort with human papilloma virus-related oropharyngeal cancer (HPV OPC). DW-MRI (ADCmax and ADCmin) and 18 F-FDG PET/CT (SUVmax and SUVmax ratio to liver) parameters were measured at the site of primary tumors (n = 48) and the largest lymph nodes (n = 52). Kendall's tau evaluated the correlation between DW-MRI and 18 F-FDG PET/CT parameters. Mann-Whitney test compared the post-CRT PET/CT and DW-MRI parameters between those participants with and without 2-year disease-free survival (DFS).

RESULTS

There was no correlation between DW-MRI and 18 F-FDG PET/CT parameters on 12-week posttreatment imaging (P = .455-.794; tau = -0.075-0.25) or their interval changes from pretreatment to 12-week posttreatment imaging (P = .1-.946; tau = -0.194-0.044). The primary tumor ADCmean (P = .03) and the interval change in nodal ADCmin (P = .05) predicted 2-year DFS but none of the 18 F-FDG PET/CT parameters were associated with 2-year DFS.

CONCLUSIONS

There is no correlation between the quantitative DWI-MRI and 18 F-FDG PET/CT parameters derived from 12-week post-CRT studies. These parameters may be independent biomarkers however in this HPV OPC dominant cohort, only selected ADC parameters demonstrated prognostic significance. Study was prospectively registered at http://www.controlled-trials.com/ISRCTN58327080.

Understanding diffusion-weighted MRI analysis: Repeatability and performance of diffusion models in a benign breast lesion cohort

Diffusion-weighted MRI (DWI) is an important tool for oncology research, with great clinical potential for the classification and monitoring of breast lesions. The utility of parameters derived from DWI, however, is influenced by specific analysis choices. The purpose of this study was to critically evaluate repeatability and curve-fitting performance of common DWI signal representations, for a prospective cohort of patients with benign breast lesions. Twenty informed, consented patients with confirmed benign breast lesions underwent repeated DWI (3 T) using: sagittal single-shot spin-echo echo planar imaging, bipolar encoding, TR/TE: 11,600/86 ms, FOV: 180 x 180 mm, matrix: 90 x 90, slices: 60 x 2.5 mm, iPAT: GRAPPA 2, fat suppression, and 13 b-values: 0-700 s/mm² . A phase-reversed scan (b = 0 s/mm² ) was acquired for distortion correction. Voxel-wise repeat-measures coefficients of variation (CoVs) were derived for monoexponential (apparent diffusion coefficient [ADC]), biexponential (intravoxel incoherent motion: f, D, D*) and stretched exponential (α, DDC) across the parameter histograms for lesion regions of interest (ROIs). Goodness-of-fit for each representation was assessed by Bayesian information criterion. The volume of interest (VOI) definition was repeatable (CoV 13.9%). Within lesions, and across both visits and the cohort, there was no dominant best-fit model, with all representations giving the best fit for a fraction of the voxels. Diffusivity measures from the signal representations (ADC, D, DDC) all showed good repeatability (CoV < 10%), whereas parameters associated with pseudodiffusion (f, D*) performed poorly (CoV > 50%). The stretching exponent α was repeatable (CoV < 12%). This pattern of repeatability was consistent over the central part of the parameter percentiles. Assumptions often made in diffusion studies about analysis choices will influence the detectability of changes, potentially obscuring useful information. No single signal representation prevails within or across lesions, or across repeated visits; parameter robustness is therefore a critical consideration. Our results suggest that stretched exponential representation is more repeatable than biexponential, with pseudodiffusion parameters unlikely to provide clinically useful biomarkers.

Prognostic value of diffusion-weighted magnetic resonance imaging of brain in fetal growth restriction: results of prospective multicenter study

OBJECTIVE

To measure prospectively apparent diffusion coefficient (ADC) values between 28 and 32 weeks of gestation in different cerebral territories of fetuses with estimated fetal weight (EFW) ≤ 5^th centile, and analyze their association with adverse perinatal outcome.

METHODS

This was a prospective study involving six tertiary-level perinatal centers. In the period 22 November 2016 to 11 September 2017, we included singleton, small-for-gestational-age (SGA) fetuses with EFW ≤ 5^th percentile, between 28 and 32 weeks of gestation, regardless of the umbilical artery Doppler and maternal uterine artery Doppler findings. A fetal magnetic resonance imaging (MRI) examination with diffusion-weighted sequences (DWI) was performed within 14 days following inclusion and before 32 weeks. ADC values were calculated in the frontal and occipital white matter, basal ganglia and cerebellar hemispheres. An ultrasound examination was performed within 1 week prior to the MRI examination. The primary outcome was a composite measure of adverse perinatal outcome, defined as any of the following: perinatal death; admission to neonatal intensive care unit with mechanical ventilation > 48 h; necrotizing enterocolitis; Grade III-IV intraventricular hemorrhage; periventricular leukomalacia. A univariate comparison of median ADC values in all cerebral territories between fetuses with and those without adverse perinatal outcome was performed. The association between ADC values and adverse perinatal outcome was then analyzed using multilevel logistic regression models to adjust for other common prognostic factors for growth-restricted fetuses.

RESULTS

MRI was performed in 64 patients, of whom five were excluded owing to fetal movement artifacts on DWI and two were excluded for termination of pregnancy with no link to fetal growth restriction (FGR). One intrauterine death occurred secondary to severe FGR. Among the 56 liveborn neonates, delivered at a mean ± SD gestational age of 33.6 ± 3.0 weeks, with a mean birth weight of 1441 ± 566 g, four neonatal deaths occurred. In addition, two neonates required prolonged mechanical ventilation, one of whom also developed necrotizing enterocolitis. Overall, therefore, seven out of 57 (12.3%) cases had an adverse perinatal outcome (95% CI, 3.8-20.8%). The ADC values in the frontal region were significantly lower in the group with adverse perinatal outcome vs those in the group with favorable outcome (mean values of both hemispheres, 1.68 vs 1.78 × 10^-3  mm² /s; P = 0.04). No significant difference in ADC values was observed between the two groups in any other cerebral territory. A cut-off value of 1.70 × 10^-3  mm² /s was associated with a sensitivity of 57% (95% CI, 18-90%), a specificity of 78% (95% CI, 63-88%), a positive predictive value of 27% (95% CI, 8-55%) and a negative predictive value of 93% (95% CI, 80-98%) for the prediction of adverse perinatal outcome. A mean frontal ADC value < 1.70 × 10^-3  mm² /s was not associated significantly with an increased risk of adverse perinatal outcome, either in the univariate analysis (P = 0.07), or when adjusting for gestational age at MRI and fetal sex (odds ratio (OR), 6.06 (95% CI, 0.9-37.1), P = 0.051) or for umbilical artery Doppler (OR, 6.08 (95% CI, 0.89-41.44)).

CONCLUSION

This first prospective, multicenter, cohort study using DWI in the setting of SGA found lower ADC values in the frontal white-matter territory in fetuses with, compared with those without, adverse perinatal outcome. To determine the prognostic value of these changes, further standardized evaluation of the neurodevelopment of children born with growth restriction is required. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

The prognosis of brain magnetic resonance imaging injury pattern for outcomes of hypothermia-treated infants

Magnetic resonance imaging (MRI) can be a tool that allows the observation of structural injury patterns after cooling. The aim of this study was to determine the early pattern of brain injury in the MRIs of infants with hypoxic ischemic encephalopathy (HIE) after cooling and to search for any clinical factors related to abnormal MRI findings.The study retrospectively recruited 118 infants who were treated with therapeutic hypothermia (TH) between 2013 and 2016.Forty-three patients had normal brain MRI, and 75 had abnormal brain MRI findings. The TH-treated infants with abnormal brain MRI readings showed significantly more clinical seizures and the use of additional antiepileptic drugs (AEDs) than the normal MRI group. As a long-term outcome, more lesions in the basal ganglia and thalamus, posterior limb of internal capsule, or severe white matter lesions were associated with abnormal neurodevelopmental outcomes at 18 to 24 months of age.A higher frequency of clinical seizures and AED use were related to abnormal brain injury on MRI. A significant risk for poor long-term outcomes was found in the abnormal brain MRI group.

Pretreatment apparent diffusion coefficient does not predict therapy response to neoadjuvant chemotherapy in breast cancer

Background

Some reports indicated that apparent diffusion coefficient can predict pathologic response to treatment in breast cancer (BC). The purpose of the present meta-analysis was to provide evident data regarding use of ADC values for prediction of treatment response in BC.

Methods

MEDLINE library, EMBASE and SCOPUS databases were screened for associations between ADC and treatment response for neoadjuvant chemotherapy in breast cancer (BC) up to March 2020. Overall, 22 studies met the inclusion criteria. For the present analysis, the following data were extracted from the collected studies: authors, year of publication, study design, number of patients/lesions, mean and standard deviation of the pretreatment ADC values. The methodological quality of the included studies was checked according to the QUADAS-2 instrument. The meta-analysis was undertaken by using RevMan 5.3 software. DerSimonian and Laird random-effects models with inverse-variance weights were used without any further correction to account for the heterogeneity between the studies. Mean ADC values including 95% confidence intervals were calculated separately for responders and non responders.

Results

The acquired 22 studies comprised 1827 patients with different BC. Of the 1827 patients, 650 (35.6%) were reported as responders and 1177 (64.4%) as non-responders to the neoadjuvant chemotherapy. The pooled calculated pretreatment mean ADC value of BC in responders was 0.98 (95% CI = [0.94; 1.03]). In non-responders, it was 1.05 (95% CI = [1.00; 1.10]). The ADC values of the groups overlapped significantly.

Conclusion

Pretreatment ADC alone cannot predict response to neoadjuvant chemotherapy in BC.

Micro-structure diffusion scalar measures from reduced MRI acquisitions

In diffusion MRI, the Ensemble Average diffusion Propagator (EAP) provides relevant micro-structural information and meaningful descriptive maps of the white matter previously obscured by traditional techniques like Diffusion Tensor Imaging (DTI). The direct estimation of the EAP, however, requires a dense sampling of the Cartesian q-space involving a huge amount of samples (diffusion gradients) for proper reconstruction. A collection of more efficient techniques have been proposed in the last decade based on parametric representations of the EAP, but they still imply acquiring a large number of diffusion gradients with different b-values (shells). Paradoxically, this has come together with an effort to find scalar measures gathering all the q-space micro-structural information probed in one single index or set of indices. Among them, the return-to-origin (RTOP), return-to-plane (RTPP), and return-to-axis (RTAP) probabilities have rapidly gained popularity. In this work, we propose the so-called "Apparent Measures Using Reduced Acquisitions" (AMURA) aimed at computing scalar indices that can mimic the sensitivity of state of the art EAP-based measures to micro-structural changes. AMURA drastically reduces both the number of samples needed and the computational complexity of the estimation of diffusion properties by assuming the diffusion anisotropy is roughly independent from the radial direction. This simplification allows us to compute closed-form expressions from single-shell information, so that AMURA remains compatible with standard acquisition protocols commonly used even in clinical practice. Additionally, the analytical form of AMURA-based measures, as opposed to the iterative, non-linear reconstruction ubiquitous to full EAP techniques, turns the newly introduced apparent RTOP, RTPP, and RTAP both robust and efficient to compute.

Determination of optimized set of b-values for Apparent Diffusion Coefficient mapping in liver Diffusion-Weighted MRI

In this manuscript we derive the Cramér-Rao Lower Bound (CRLB) of the monoexponential diffusion-weighted signal model under a realistic noise assumption, and propose a formulation to obtain optimized sets of b-values that maximize the noise performance of the Apparent Diffusion Coefficient (ADC) maps given a target ADC and a signal-to-noise ratio. Therefore, for various sets of parameters (S₀ and ADC), signal-to-noise ratios (SNR) and noise distribution, we computed optimized sets of b-values using CRLB-based analysis in two different ways: (i) through a greedy algorithm where b-values from a pool of candidates were added iteratively to the set, and (ii) through a two b-value search algorithm were all two b-value combinations of the pool of candidates were tested. Further, optimized sets of b-values were computed from synthetic data, phantoms, and in-vivo liver diffusion-weighted imaging (DWI) experiments to validate the CRLB-based analysis. The optimized sets of b-values obtained through the proposed CRLB-based analysis showed good agreement with the optimized sets obtained experimentally from synthetic, phantoms, and in-vivo liver data. The variance of the ADC maps decreased when employing the optimized set of b-values compared to various sets of b-values proposed in the literature for in-vivo liver DWI, although differences of notable magnitude between noise models and optimization strategies were not found. In addition, the higher b-values decreased for lower SNR under the Rician noise distribution. Optimization of the set b-values is critical to maximize the noise performance (i.e., maximize the precision and minimize the variance) of the estimated ADC maps in diffusion-weighted MRI. Hence, the proposed approach may help to optimize and standardize liver diffusion-weighted MRI acquisitions by computing optimized set of b-values for a given set of parameters.

Radiological analysis of breast lymphoma: Experiences from cases series studies

This retrospective study aimed to improve the diagnostic accuracy of breast lymphoma (BL) by analyzing the findings of BL on mammography and magnetic resonance imaging (MRI).Fifteen patients with breast lymphoma (BL, Primary/Secondary: 13/2) were confirmed by pathology. The imaging findings of those patients were analyzed by 2 senior radiologists.BL commonly showed significant enhancement with penetrating vessels and septation in masses on dynamic contrast-enhanced MRI (DCE-MRI). Diffusion limitation of BL is more pronounced than breast cancer on diffusion weighted imaging.The study suggests that the penetrating vessels and diffusion restriction of lesions are helpful for the diagnosis and differential diagnosis of BL.

Textural features on 18F-FDG PET/CT and dynamic contrast-enhanced MR imaging for predicting treatment response and survival of patients with hypopharyngeal carcinoma

The utility of multimodality molecular imaging for predicting treatment response and survival of patients with hypopharyngeal carcinoma remains unclear. Here, we sought to investigate whether the combination of different molecular imaging parameters may improve outcome prediction in this patient group.Patients with pathologically proven hypopharyngeal carcinoma scheduled to undergo chemoradiotherapy (CRT) were deemed eligible. Besides clinical data, parameters obtained from pretreatment 2-deoxy-2-[fluorine-18]fluoro-D-glucose positron emission tomography/computed tomography (F-FDG PET/CT), dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), and diffusion-weighted MRI were analyzed in relation to treatment response, recurrence-free survival (RFS), and overall survival (OS).A total of 61 patients with advanced-stage disease were examined. After CRT, 36% of the patients did not achieve a complete response. Total lesion glycolysis (TLG) and texture feature entropy were found to predict treatment response. The transfer constant (K), TLG, and entropy were associated with RFS, whereas K, blood plasma volume (Vp), standardized uptake value (SUV), and entropy were predictors of OS. Different scoring systems based on the sum of PET- or MRI-derived prognosticators enabled patient stratification into distinct prognostic groups (P <.0001). The complete response rate of patients with a score of 2 was significantly lower than those of patients with a score 1 or 0 (14.7% vs 58.9% vs 75.7%, respectively, P = .007, respectively). The combination of PET- and DCE-MRI-derived independent risk factors allowed a better survival stratification than the TNM staging system (P <.0001 vs .691, respectively).Texture features on F-FDG PET/CT and DCE-MRI are clinically useful to predict treatment response and survival in patients with hypopharyngeal carcinoma. Their combined use in prognostic scoring systems may help these patients benefit from tailored treatment and obtain better oncological results.

Change in Apparent Diffusion Coefficient Is Associated With Local Failure After Stereotactic Body Radiation Therapy for Non-Small Cell Lung Cancer: A Prospective Clinical Trial

PURPOSE

Response assessment with computed tomography after stereotactic body radiation therapy (SBRT) for non-small cell lung cancer (NSCLC) is challenging because myriad anatomic changes can occur after treatment. Diffusion-weighted magnetic resonance imaging (MRI) may provide additional data to guide therapy response. The primary objective was to evaluate the effect of SBRT on the mean apparent diffusion coefficient (ADC).

METHODS AND MATERIALS

This is a prospective clinical study of patients with NSCLC who received SBRT to the primary lung lesion. Patients underwent MRI scans before and at 1 month after completion of SBRT. MRI consisted of T1- and T2-weighted sequences, along with postcontrast, dynamic-contrast, and diffusion-weighted sequences with construction of ADC maps. Two blinded radiologists generated the ADC. SBRT was given over 5 fractions.

RESULTS

A total of 13 patients were enrolled. Twelve patients were eligible for analysis. An average increase of 50% and 46% in mean single-plane ADC was observed after treatment by readers 1 and 2, respectively (P < .01, both reviewers). There was good interobserver agreement of single-plane ADC values between the 2 radiologists (Pearson correlation of 0.85 [baseline] and 0.89 [1-month post-SBRT], P < .001 for both). There was also a significant 18% increase in mean volumetric ADC on the 1-month scan (Wilcoxon P = .02). Two patients developed a local failure after SBRT, 1 at 6 months and the other at 34 months. Using a threshold of volumetric ADC increase of greater than 40%, 2 of 2 patients demonstrated local failure compared with 0 of 10 patients below this limit.

CONCLUSIONS

A statistically significant increase in ADC was observed 1 month after treatment. An ADC increase of 40% at 1 month was associated with a higher rate of local failure. This pilot study provides impetus for studying ADC as a radiomic biomarker in patients receiving lung SBRT for NSCLC.

A Meta-analysis of the Diagnostic Performance of Diffusion MRI for Breast Lesion Characterization

Background Various techniques are available to assess diffusion properties of breast lesions as a marker of malignancy at MRI. The diagnostic performance of these diffusion markers has not been comprehensively assessed. Purpose To compare by meta-analysis the diagnostic performance of parameters from diffusion-weighted imaging (DWI), diffusion-tensor imaging (DTI), and intravoxel incoherent motion (IVIM) in the differential diagnosis of malignant and benign breast lesions. Materials and Methods PubMed and Embase databases were searched from January to March 2018 for studies in English that assessed the diagnostic performance of DWI, DTI, and IVIM in the breast. Studies were reviewed according to eligibility and exclusion criteria. Publication bias and heterogeneity between studies were assessed. Pooled summary estimates for sensitivity, specificity, and area under the curve were obtained for each parameter by using a bivariate model. A subanalysis investigated the effect of MRI parameters on diagnostic performance by using a Student t test or a one-way analysis of variance. Results From 73 eligible studies, 6791 lesions (3930 malignant and 2861 benign) were included. Publication bias was evident for studies that evaluated apparent diffusion coefficient (ADC). Significant heterogeneity (P < .05) was present for all parameters except the perfusion fraction (f). The pooled sensitivity, specificity, and area under the curve for ADC was 89%, 82%, and 0.92, respectively. The highest performing parameter for DTI was the prime diffusion coefficient (λ1), and pooled sensitivity, specificity, and area under the curve was 93%, 90%, and 0.94, respectively. The highest performing parameter for IVIM was tissue diffusivity (D), and the pooled sensitivity, specificity, and area under the curve was 88%, 79%, and 0.90. Choice of MRI parameters had no significant effect on diagnostic performance. Conclusion Diffusion-weighted imaging, diffusion-tensor imaging, and intravoxel incoherent motion have comparable diagnostic accuracy with high sensitivity and specificity. Intravoxel incoherent motion is comparable to apparent diffusion coefficient. Diffusion-tensor imaging is potentially promising but to date the number of studies is limited. © RSNA, 2019 Online supplemental material is available for this article.

Whole-lesion ADC histogram analysis is not able to reflect microvessel density in HNSCC

Diffusion-weighted imaging (DWI) is a functional imaging technique sensitive to microstructure in tissues. It is widely acknowledged to reflect cellularity in tumors. A small part of DWI is also sensitive to perfusion-related information and might therefore be also be able to reflect microvessel density in tumor tissues. Aim of the present study was to elucidate possible correlations between microvessel density and apparent diffusion coefficient (ADC) values in head and neck squamous cell carcinoma (HNSCC).Thirty-four patients with histologically proven primary HNSCC were included in the study. DWI was performed with a 3 T magnetic resonance imaging (MRI) (b-values 0 and 800 s/mm) and histogram analysis was calculated with a whole lesion measurement. In every case, microvessel density was estimated with CD105-stained specimens.There were no statistically significant correlations between ADC histogram parameters and microvessel density. The calculated correlation coefficients ranged from r = -0.27, P = .13 for entropy and vessel area to r = 0.16, P = .40 for ADCmin and vessel count.Whole-lesion histogram analysis of ADC values cannot reflect microvessel density in HNSCC.

Accuracy of Diffusion-weighted Magnetic Resonance Imaging in Detecting Mucosal Healing and Treatment Response, and in Predicting Surgery, in Crohn's Disease

BACKGROUND AND AIMS

The Nancy score is a luminal Crohn's disease [CD] activity index applied in diffusion-weighted magnetic resonance imaging [DW-MRI]. We assessed the accuracy of the Nancy score in detecting mucosal healing and treatment response, and in predicting surgery.

METHODS

This was a retrospective, single-centre study of all patients with active CD and serial DW-MRI before and after treatment initiation with a biologic drug, between January 2010 and September 2016. The gold standard was endoscopy. The association between the Nancy score and the cumulative probability of intestinal resection during follow-up was tested combining Kaplan-Meier curves and log-rank testing.

RESULTS

A total of 96 patients were included; 20 had concomitantly undergone endoscopy. The Nancy score correlated well with the Crohn's Disease Endoscopic Index of Severity [r = 0.60 for the total score and r = 0.63 for the segmental score]. A total Nancy score <6 and a segmental Nancy score <2 detected mucosal healing with an area under the receiver operating characteristic curve [AUROC] of 0.82 (95% confidence interval [CI] 0.69-0.94, p <0.0001) and 0.80 [95% CI 0.73-0.87, p <0.0001], respectively. The Nancy score was highly sensitive to changes [Guyatt's responsiveness indices: 1.18 for the total score and 0.85 for the segmental score]. Mucosal healing on DW-MRI after treatment initiation was associated with a lower cumulative probability of intestinal surgery (p = 0.0251, median [interquartile range: IQR] follow-up 2.2 [1.6-3.7] years).

CONCLUSIONS

In CD, the Nancy score accurately detects mucosal healing and treatment response, the latter associated with a lower likelihood of intestinal resection.

Diagnostic value of diffusion-weighted magnetic resonance imaging for local and skull base recurrence of nasopharyngeal carcinoma after radiotherapy

Tumor recurrence is a major cause of nasopharyngeal carcinoma (NPC) treatment failure. Diffusion-weighted imaging (DWI) is used for a variety of cancers, but few data are available for NPC.The aim of the study was to investigate the DWI features of recurrent NPC after radiotherapy and apparent diffusion coefficient (ADC) thresholds for the diagnosis of recurrent NPC.This was a retrospective study of 160 patients with NPC treated by radiotherapy at the Cancer Hospital affiliated to Guangxi Medical University from May 2012 to March 2015. The patients were divided into the local recurrence (n = 39), fibrosis (n = 51), clivus recurrence (n = 22), and clivus nonrecurrence (n = 48) groups. The patients underwent magnetic resonance imaging (MRI), enhanced MRI, and DWI. Receiver operating characteristics curves were used to determine sensitivity, specificity, and negative predictive values.ADC values were significantly different between the recurrence and fibrosis groups (P < .0001). Using ADC threshold values of 0.887 × 10 mm/s for local recurrence, the area under the curve (AUC) of DWI was 0.967 (87.2% sensitivity and 94.1% specificity), compared with 0.732 for routine MRI (71.8% sensitivity and 74.5% specificity) (P < .001). Using ADC threshold values of 1.018 × 10 mm/s for the diagnosis of clivus recurrent NPC, the AUC of DWI was 0.984 (95.5% sensitivity and 91.7% specificity) compared with 0.558 for routine MRI (63.6% sensitivity and 47.9% specificity) (P < .001).DWI has a higher diagnostic value for recurrent NPC than MRI. DWI can increase the diagnosis sensitivity and specificity of locally recurrent NPC.

Diagnostic performance of intravoxel incoherent motion diffusion-weighted imaging and dynamic contrast-enhanced MRI for assessment of anal fistula activity

Objective

To evaluate intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) sequences for quantitative characterization of anal fistula activity.

Methods

This retrospective study was approved by the institutional review board. One hundred and two patients underwent MRI for clinical suspicion of anal fistula. Forty-three patients with demonstrable anal fistulas met the inclusion criteria. Quantitative analysis included measurement of DCE and IVIM parameters. The reference standard was clinical activity based on medical records. Statistical analyses included Bayesian analysis with Markov Chain Monte Carlo, multivariable logistic regression, and receiver operating characteristic analyses.

Results

Brevity of enhancement, defined as the time difference between the wash-in and wash-out, was longer in active than inactive fistulas (p = 0.02). Regression coefficients of multivariable logistic regression analysis revealed that brevity of enhancement increased and normalized perfusion area under curve decreased with presence of active fistulas (p = 0.03 and p = 0.04, respectively). By cross-validation, a logistic regression model that included quantitative perfusion parameters (DCE and IVIM) performed significantly better than IVIM only (p < 0.001). Area under the curves for distinguishing patients with active from those with inactive fistulas were 0.669 (95% confidence interval [CI]: 0.500, 0.838) for a model with IVIM only, 0.860 (95% CI: 0.742, 0.977) for a model with IVIM and brevity of enhancement, and 0.921 (95% CI: 0.846, 0.997) for a model with IVIM and all DCE parameters.

Conclusion

The inclusion of brevity of enhancement measured by DCE-MRI improved assessment of anal fistula activity over IVIM-DWI only.

[Value of functional magnetic resonance imaging in predicting outcomes of neoadjuvant chemoradiotherapy in rectal cancer]

Rectal cancer is one of the common cancers which poses a threat to the health of mankind. In recent years. Multi-modality treatment strategies for locally advanced rectal cancer improve the treatment efficiency. Accurate prediction of the treatment response after the neoadjuvant chemoradiotherapy (CRT) can guide more suitable treatment strategy. MERCURY study proved the prognostic value of post-CRT standard morphologic MRI(T2-weighted) assessment of tumor regression grade(TRG), and MRI assessment of circumferential resection margin can guide the definitive surgery. Compared with standard morphologic MRI (T2-weighted), functional MRI, including diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE) MRI, has shown more promising results for the prediction of therapeutic response in rectal cancer. The addition of diffusion-weighted images to T2-weighted images improves the accuracy of restaging examinations for determination of complete pathologic responders. DCE can reflect the tumor micro-vascular environment, and the change of perfusion in response to treatment. These images have the potential to improve the accuracy of therapeutic response in rectal cancer.

Repeatability of derived parameters from histograms following non-Gaussian diffusion modelling of diffusion-weighted imaging in a paediatric oncological cohort

OBJECTIVES

To examine repeatability of parameters derived from non-Gaussian diffusion models in data acquired in children with solid tumours.

METHODS

Paediatric patients (<16 years, n = 17) were scanned twice, 24 h apart, using DWI (6 b-values, 0-1000 mm-2 s) at 1.5 T in a prospective study. Tumour ROIs were drawn (3 slices) and all data fitted using IVIM, stretched exponential, and kurtosis models; percentage coefficients of variation (CV) calculated for each parameter at all ROI histogram centiles, including the medians.

RESULTS

The values for ADC, D, DDCα, α, and DDCK gave CV < 10 % down to the 5th centile, with sharp CV increases below 5th and above 95th centile. K, f, and D* showed increased CV (>30 %) over the histogram. ADC, D, DDCα, and DDCK were strongly correlated (ρ > 0.9), DDCα and α were not correlated (ρ = 0.083).

CONCLUSION

Perfusion- and kurtosis-related parameters displayed larger, more variable CV across the histogram, indicating observed clinical changes outside of D/DDC in these models should be interpreted with caution. Centiles below 5th for all parameters show high CV and are unreliable as diffusion metrics. The stretched exponential model behaved well for both DDCα and α, making it a strong candidate for modelling multiple-b-value diffusion imaging data.

KEY POINTS

• ADC has good repeatability as low 5th centile of the histogram distribution. • High CV was observed for all parameters at extremes of histogram. • Parameters from the stretched exponential model showed low coefficients of variation. • The median ADC, D, DDC α , and DDC K are highly correlated and repeatable. • Perfusion/kurtosis parameters showed high CV variations across their histogram distributions.

[Comparison of Analytical Values in Diffusion Kurtosis Imaging among Different MRI Units]

Diffusion kurtosis imaging (DKI) is a method of analyzing restricted diffusion. Mean kurtosis (MK) is obtained from DKI. It is not known how different MRI scanners and coil systems will change MK when the same imaging parameters are used. The purpose of this study is to identify tendencies in MK when using various MRI scanners and coil systems. A total of 27 healthy volunteers were enrolled in this study. DKI was performed on the brain for each volunteer on five MRI scanner/coil system combinations using the same scan parameters. MK of 10 anatomical areas of the brain were compared, and the signal-noise ratios (SNRs) of b-2000 s/mm² images were measured in identical areas. There were no significant differences among MKs from multi transmit (MT) MRI systems, but MK was significantly lower on the single transmit MRI system because of pepper artifact caused by low SNR. In conclusion, we found no significant differences in MK among MT systems, and MK was significantly lower without MT.

Test-retest reliability of high angular resolution diffusion imaging acquisition within medial temporal lobe connections assessed via tract based spatial statistics, probabilistic tractography and a novel graph theory metric

This study examined the reliability of high angular resolution diffusion tensor imaging (HARDI) data collected on a single individual across several sessions using the same scanner. HARDI data was acquired for one healthy adult male at the same time of day on ten separate days across a one-month period. Environmental factors (e.g. temperature) were controlled across scanning sessions. Tract Based Spatial Statistics (TBSS) was used to assess session-to-session variability in measures of diffusion, fractional anisotropy (FA) and mean diffusivity (MD). To address reliability within specific structures of the medial temporal lobe (MTL; the focus of an ongoing investigation), probabilistic tractography segmented the Entorhinal cortex (ERc) based on connections with Hippocampus (HC), Perirhinal (PRc) and Parahippocampal (PHc) cortices. Streamline tractography generated edge weight (EW) metrics for the aforementioned ERc connections and, as comparison regions, connections between left and right rostral and caudal anterior cingulate cortex (ACC). Coefficients of variation (CoV) were derived for the surface area and volumes of these ERc connectivity-defined regions (CDR) and for EW across all ten scans, expecting that scan-to-scan reliability would yield low CoVs. TBSS revealed no significant variation in FA or MD across scanning sessions. Probabilistic tractography successfully reproduced histologically-verified adjacent medial temporal lobe circuits. Tractography-derived metrics displayed larger ranges of scanner-to-scanner variability. Connections involving HC displayed greater variability than metrics of connection between other investigated regions. By confirming the test retest reliability of HARDI data acquisition, support for the validity of significant results derived from diffusion data can be obtained.

Added Value of Stroke Protocol MRI Following Negative Initial CT in the Acute Stroke Setting

The aim of the study was to determine the added value of stroke protocol MRI following negative initial CT brain in the acute stroke setting. A retrospective study was performed over a 6 month period in a tertiary referral stroke centre. Patients were selected from the stroke and radiology databases. Inclusion criteria: clinical stroke syndrome, negative initial CT with subsequent MRI study with diffusion weighted sequences. Ninety two patients were reviewed and 73 (M:F of 39:34, mean age 62.1 ± 14.0 years) met the inclusion criteria. Twenty MRI studies (27.4%) were positive for acute/subacute ischaemia in the setting of a normal initial CT. The average time interval between initial CT and MRI brain imaging was 4.7 ± 2.6 days. Whilst CT continues to be the first line imaging investigation for acute stroke, MRI has substantial added value following negative initial CT in the diagnosis of stroke.

The value of blood oxygenation level-dependent (BOLD) MR imaging in differentiation of renal solid mass and grading of renal cell carcinoma (RCC): analysis based on the largest cross-sectional area versus the entire whole tumour

Objectives

To study the value of assessing renal masses using different methods in parameter approaches and to determine whether BOLD MRI is helpful in differentiating RCC from benign renal masses, differentiating clear-cell RCC from renal masses other than clear-cell RCC and determining the tumour grade.

Methods

Ninety-five patients with 139 renal masses (93 malignant and 46 benign) who underwent abdominal BOLD MRI were enrolled. R2* values were derived from the largest cross-section (R2*_largest) and from the whole tumour (R2*_whole). Intra-observer and inter-observer agreements were analysed based on two measurements by the same observer and the first measurement from each observer, respectively, and these agreements are reported with intra-class correlation coefficients and 95% confidence intervals. The diagnostic value of the R2* value in the evaluation was assessed with receiver-operating characteristic analysis.

Results

The intra-observer agreement was very good for R2*_largest and R2*_whole (all > 0.8). The inter-observer agreement of R2*_whole (0.75, 95% confidence interval: 0.69~0.79) was good and was significantly improved compared with the R2*_largest (0.61, 95% confidence interval: 0.52~0.68), as there was no overlap in the 95% confidence interval of the intra-class correlation coefficients. The diagnostic value in differentiating renal cell carcinoma from benign lesions with R2*_whole (AUC=0.79/0.78[observer1/observer2]) and R2*_largest (AUC=0.75[observer1]) was good and significantly higher (p=0.01 for R2*_largest[observer2] vs R2*_whole[observer2], p<0.01 for R2*_whole[observer1] vs R2*_largest[observer2]) than R2*_largest for observer 2 (AUC=0.64). For the grading of clear-cell RCC, both R2*_whole and R2*_largest were good (all > 0.7) and were not significantly different (p=0.89/0.93 for R2*largest vs R2*whole[observer1/observer2], 0.96 for R2*whole[observer1] vs R2*largest[observer2] and 0.96 for R2*whole [observer2] vs R2*largest[observer1]).

Conclusions

BOLD MRI could provide a feasible parameter for differentiating renal cell carcinoma from benign renal masses and for predicting clear-cell renal cell carcinoma grading. Compared with the largest cross-section, assessing the whole tumour provides better inter-observer agreement in parameter measurement for differentiating renal cell carcinoma from benign renal masses.

Assessment of non-Gaussian diffusion with singly and doubly stretched biexponential models of diffusion-weighted MRI (DWI) signal attenuation in prostate tissue

Non-Gaussian diffusion dynamics was investigated in the two distinct water populations identified by a biexponential model of diffusion in prostate tissue. Diffusion-weighted MRI (DWI) signal attenuation was measured ex vivo in two formalin-fixed prostates at 9.4 T with diffusion times Δ = 10, 20 and 40 ms, and b values in the range 0.017-8.2 ms/µm(2) . A conventional biexponential model was compared with models in which either the lower diffusivity component or both of the components of the biexponential were stretched. Models were compared using Akaike's Information Criterion (AIC) and a leave-one-out (LOO) test of model prediction accuracy. The doubly stretched (SS) model had the highest LOO prediction accuracy and lowest AIC (highest information content) in the majority of voxels at Δ = 10 and 20 ms. The lower diffusivity stretching factor (α2 ) of the SS model was consistently lower (range ~0.3-0.9) than the higher diffusivity stretching factor (α1 , range ~0.7-1.1), indicating a high degree of diffusion heterogeneity in the lower diffusivity environment, and nearly Gaussian diffusion in the higher diffusivity environment. Stretched biexponential models demonstrate that, in prostate tissue, the two distinct water populations identified by the simple biexponential model individually exhibit non-Gaussian diffusion dynamics.

Quantitative assessment of diffusional kurtosis anisotropy

Diffusional kurtosis imaging (DKI) measures the diffusion and kurtosis tensors to quantify restricted, non-Gaussian diffusion that occurs in biological tissue. By estimating the kurtosis tensor, DKI accounts for higher order diffusion dynamics, when compared with diffusion tensor imaging (DTI), and consequently can describe more complex diffusion profiles. Here, we compare several measures of diffusional anisotropy which incorporate information from the kurtosis tensor, including kurtosis fractional anisotropy (KFA) and generalized fractional anisotropy (GFA), with the diffusion tensor-derived fractional anisotropy (FA). KFA and GFA demonstrate a net enhancement relative to FA when multiple white matter fiber bundle orientations are present in both simulated and human data. In addition, KFA shows net enhancement in deep brain structures, such as the thalamus and the lenticular nucleus, where FA indicates low anisotropy. Thus, KFA and GFA provide additional information relative to FA with regard to diffusional anisotropy, and may be particularly advantageous for the assessment of diffusion in complex tissue environments.

Glioma: application of whole-tumor texture analysis of diffusion-weighted imaging for the evaluation of tumor heterogeneity

BACKGROUND AND PURPOSE

To apply a texture analysis of apparent diffusion coefficient (ADC) maps to evaluate glioma heterogeneity, which was correlated with tumor grade.

MATERIALS AND METHODS

Forty patients with glioma (WHO grade II (n = 8), grade III (n = 10) and grade IV (n = 22)) underwent diffusion-weighted imaging (DWI), and the corresponding ADC maps were obtained. Regions of interest containing the lesions were drawn on every section of the ADC map containing the tumor, and volume-based data of the entire tumor were constructed. Texture and first order features including entropy, skewness and kurtosis were derived from the ADC map using in-house software. A histogram analysis of the ADC map was also performed. The texture and histogram parameters were compared between low-grade and high-grade gliomas using an unpaired student's t-test. Additionally, a one-way analysis of variance analysis with a post-hoc test was performed to compare the parameters of each grade.

RESULTS

Entropy was observed to be significantly higher in high-grade gliomas than low-grade tumors (6.861±0.539 vs. 6.261±0.412, P  = 0.006). The fifth percentiles of the ADC cumulative histogram also showed a significant difference between high and low grade gliomas (836±235 vs. 1030±185, P = 0.037). Only entropy proved to be significantly different between grades III and IV (6.295±0.4963 vs. 7.119±0.3165, P<0.001). The diagnostic accuracy of ADC entropy was significantly higher than that of the fifth percentile of the ADC histogram (P = 0.0034) in distinguishing high- from low-grade glioma.

CONCLUSION

A texture analysis of the ADC map based on the entire tumor volume can be useful for evaluating glioma grade, which provides tumor heterogeneity.

The evolving role of diffusion magnetic resonance imaging in movement disorders

Significant advances have allowed diffusion magnetic resonance imaging (MRI) to evolve into a powerful tool in the field of movement disorders that can be used to study disease states and connectivity between brain regions. Diffusion MRI is a promising potential biomarker for Parkinson's disease and other forms of parkinsonism, and may allow the distinction of different forms of parkinsonism. Techniques such as tractography have contributed to our current thinking regarding the pathophysiology of dystonia and possible mechanisms of penetrance. Diffusion MRI measures could potentially assist in monitoring disease progression in Huntington's disease, and in uncovering the nature of the processes and structures involved the development of essential tremor. The ability to represent structural connectivity in vivo also makes diffusion MRI an ideal adjunctive tool for the surgical treatment of movement disorders. We review recent studies using diffusion MRI in movement disorders research and present the current state of the science as well as future directions.

Effect of patient sex on white matter alterations in unilateral medial temporal lobe epilepsy with hippocampal sclerosis assessed by diffusion tensor imaging

BACKGROUND AND PURPOSE

Studies shows ictal behavior and symptoms are affected by patient sex in temporal lobe epilepsy. The purpose of our study was to determine whether alterations in the WM as assessed by DTI display different patterns in male and female patients with unilateral HS.

MATERIALS AND METHODS

Patients with unilateral HS were categorized as women with right HS (n=12), men with right HS (n=10), women with left HS (n=12), and men with left HS (n=10). DTI of the brain along 64 noncollinear directions was obtained from 44 patients and 37 sex-matched control participants. We used TBSS to analyze whole-brain WM. Regions with significant changes of FA and MD, and their mean FA, MD, total number of significant voxels, and asymmetry indices were determined for each group.

RESULTS

All groups showed bilateral and extensive reductions of FA and elevated MD in the WM, more prominent ipsilateral to the affected hippocampus. The total number of voxels with decreased FA in patients compared with that of control participants was higher in women with right HS (24,727 vs 5,459) and in men with left HS (27,332 vs 14,013) than in their counterparts. Changes in MD associated with right HS were more extensive in both men and women (right vs left HS, women: 16,926 vs 5,458; men: 5,389 vs 4,764) than in those with left HS. In patients with right HS, the ipsilateral cingulum, uncinate fasciculus, internal and external capsules, and right acoustic radiation were involved extensively in women.

CONCLUSIONS

Women and men showed different patterns in extent of WM alterations associated with HS.

Accelerating fibre orientation estimation from diffusion weighted magnetic resonance imaging using GPUs

With the performance of central processing units (CPUs) having effectively reached a limit, parallel processing offers an alternative for applications with high computational demands. Modern graphics processing units (GPUs) are massively parallel processors that can execute simultaneously thousands of light-weight processes. In this study, we propose and implement a parallel GPU-based design of a popular method that is used for the analysis of brain magnetic resonance imaging (MRI). More specifically, we are concerned with a model-based approach for extracting tissue structural information from diffusion-weighted (DW) MRI data. DW-MRI offers, through tractography approaches, the only way to study brain structural connectivity, non-invasively and in-vivo. We parallelise the Bayesian inference framework for the ball & stick model, as it is implemented in the tractography toolbox of the popular FSL software package (University of Oxford). For our implementation, we utilise the Compute Unified Device Architecture (CUDA) programming model. We show that the parameter estimation, performed through Markov Chain Monte Carlo (MCMC), is accelerated by at least two orders of magnitude, when comparing a single GPU with the respective sequential single-core CPU version. We also illustrate similar speed-up factors (up to 120x) when comparing a multi-GPU with a multi-CPU implementation.

Microstructural damage of the posterior corpus callosum contributes to the clinical severity of neglect

One theory to account for neglect symptoms in patients with right focal damage invokes a release of inhibition of the right parietal cortex over the left parieto-frontal circuits, by disconnection mechanism. This theory is supported by transcranial magnetic stimulation studies showing the existence of asymmetric inhibitory interactions between the left and right posterior parietal cortex, with a right hemispheric advantage. These inhibitory mechanisms are mediated by direct transcallosal projections located in the posterior portions of the corpus callosum. The current study, using diffusion imaging and tract-based spatial statistics (TBSS), aims at assessing, in a data-driven fashion, the contribution of structural disconnection between hemispheres in determining the presence and severity of neglect. Eleven patients with right acute stroke and 11 healthy matched controls underwent MRI at 3T, including diffusion imaging, and T1-weighted volumes. TBSS was modified to account for the presence of the lesion and used to assess the presence and extension of changes in diffusion indices of microscopic white matter integrity in the left hemisphere of patients compared to controls, and to investigate, by correlation analysis, whether this damage might account for the presence and severity of patients' neglect, as assessed by the Behavioural Inattention Test (BIT). None of the patients had any macroscopic abnormality in the left hemisphere; however, 3 cases were discarded due to image artefacts in the MRI data. Conversely, TBSS analysis revealed widespread changes in diffusion indices in most of their left hemisphere tracts, with a predominant involvement of the corpus callosum and its projections on the parietal white matter. A region of association between patients' scores at BIT and brain FA values was found in the posterior part of the corpus callosum. This study strongly supports the hypothesis of a major role of structural disconnection between the right and left parietal cortex in determining 'neglect'.

Fisher statistics for analysis of diffusion tensor directional information

A statistical approach is presented for the quantitative analysis of diffusion tensor imaging (DTI) directional information using Fisher statistics, which were originally developed for the analysis of vectors in the field of paleomagnetism. In this framework, descriptive and inferential statistics have been formulated based on the Fisher probability density function, a spherical analogue of the normal distribution. The Fisher approach was evaluated for investigation of rat brain DTI maps to characterize tissue orientation in the corpus callosum, fornix, and hilus of the dorsal hippocampal dentate gyrus, and to compare directional properties in these regions following status epilepticus (SE) or traumatic brain injury (TBI) with values in healthy brains. Direction vectors were determined for each region of interest (ROI) for each brain sample and Fisher statistics were applied to calculate the mean direction vector and variance parameters in the corpus callosum, fornix, and dentate gyrus of normal rats and rats that experienced TBI or SE. Hypothesis testing was performed by calculation of Watson's F-statistic and associated p-value giving the likelihood that grouped observations were from the same directional distribution. In the fornix and midline corpus callosum, no directional differences were detected between groups, however in the hilus, significant (p<0.0005) differences were found that robustly confirmed observations that were suggested by visual inspection of directionally encoded color DTI maps. The Fisher approach is a potentially useful analysis tool that may extend the current capabilities of DTI investigation by providing a means of statistical comparison of tissue structural orientation.

Efficient and robust nonlocal means denoising of MR data based on salient features matching

The nonlocal means (NLM) filter has become a popular approach for denoising medical images due to its excellent performance. However, its heavy computational load has been an important shortcoming preventing its use. NLM works by averaging pixels in nonlocal vicinities, weighting them depending on their similarity with the pixel of interest. This similarity is assessed based on the squared difference between corresponding pixels inside local patches centered at the locations compared. Our proposal is to reduce the computational load of this comparison by checking only a subset of salient features associated to the pixels, which suffice to estimate the actual difference as computed in the original NLM approach. The speedup achieved with respect to the original implementation is over one order of magnitude, and, when compared to more recent NLM improvements for MRI denoising, our method is nearly twice as fast. At the same time, we evidence from both synthetic and in vivo experiments that computing of appropriate salient features make the estimation of NLM weights more robust to noise. Consequently, we are able to improve the outcomes achieved with recent state of the art techniques for a wide range of realistic Signal-to-Noise ratio scenarios like diffusion MRI. Finally, the statistical characterization of the features computed allows to get rid of some of the heuristics commonly used for parameter tuning.

Analytic treatment of nuclear spin-lattice relaxation for diffusion in a cone model

We consider nuclear spin-lattice relaxation rate resulted from a diffusion equation for rotational wobbling in a cone. We show that the widespread point of view that there are no analytical expressions for correlation functions for wobbling in a cone model is invalid and prove that nuclear spin-lattice relaxation in this model is exactly tractable and amenable to full analytical description. The mechanism of relaxation is assumed to be due to dipole-dipole interaction of nuclear spins and is treated within the framework of the standard Bloemberger, Purcell, Pound-Solomon scheme. We consider the general case of arbitrary orientation of the cone axis relative the magnetic field. The BPP-Solomon scheme is shown to remain valid for systems with the distribution of the cone axes depending only on the tilt relative the magnetic field but otherwise being isotropic. We consider the case of random isotropic orientation of cone axes relative the magnetic field taking place in powders. Also we consider the cases of their predominant orientation along or opposite the magnetic field and that of their predominant orientation transverse to the magnetic field which may be relevant for, e.g., liquid crystals. Besides we treat in details the model case of the cone axis directed along the magnetic field. The latter provides direct comparison of the limiting case of our formulas with the textbook formulas for free isotropic rotational diffusion. The dependence of the spin-lattice relaxation rate on the cone half-width yields results similar to those predicted by the model-free approach.

Extremely efficient and deterministic approach to generating optimal ordering of diffusion MRI measurements

PURPOSE

Diffusion MRI measurements are typically acquired sequentially with unit gradient directions that are distributed uniformly on the unit sphere. The ordering of the gradient directions has significant effect on the quality of dMRI-derived quantities. Even though several methods have been proposed to generate optimal orderings of gradient directions, these methods are not widely used in clinical studies because of the two major problems. The first problem is that the existing methods for generating highly uniform and antipodally symmetric gradient directions are inefficient. The second problem is that the existing methods for generating optimal orderings of gradient directions are also highly inefficient. In this work, the authors propose two extremely efficient and deterministic methods to solve these two problems.

METHODS

The method for generating nearly uniform point set on the unit sphere (with antipodal symmetry) is based upon the notion that the spacing between two consecutive points on the same latitude should be equal to the spacing between two consecutive latitudes. The method for generating optimal ordering of diffusion gradient directions is based on the idea that each subset of incremental sample size, which is derived from the prescribed and full set of gradient directions, must be as uniform as possible in terms of the modified electrostatic energy designed for antipodally symmetric point set.

RESULTS

The proposed method outperformed the state-of-the-art method in terms of computational efficiency by about six orders of magnitude.

CONCLUSIONS

Two extremely efficient and deterministic methods have been developed for solving the problem of optimal ordering of diffusion gradient directions. The proposed strategy is also applicable to optimal view-ordering in three-dimensional radial MRI.

New MR imaging criteria with a diffusion-weighted sequence for the diagnosis of hepatocellular carcinoma in chronic liver diseases

BACKGROUND & AIMS

To propose MRI criteria with a diffusion-weighted imaging (DWI) sequence for the diagnosis of hepatocellular carcinoma (HCC).

METHODS

Patients, who underwent liver MRI with contrast-enhanced sequences and DWI between 2004 and 2008 and who had at least one confirmed HCC of at least 10mm, were included. Index diagnostic criteria were: (1) enhancement in the arterial-dominant phase and washout in the portal venous and/or equilibrium phases; (2) enhancement in the arterial-dominant phase and hyperintensity on DWI; (3) enhancement in the arterial-dominant phase and washout in the portal venous and/or equilibrium phases or hyperintensity on DWI. Two radiologists independently reviewed the corresponding sets of sequences (DWI alone; T1-weighted sequence before and after dynamic injection of gadolinium chelates; combined DWI-T1-weighted sequence). Inter-observer agreement and sensitivity were determined per nodule.

RESULTS

Ninety-one patients were included (109 HCCs). The sensitivity of conventional MRI criteria for the diagnosis of HCC was 59.6% for both radiologists. The sensitivity of enhancement in the arterial-dominant phase and hyperintensity on DWI was 77.1% or 76.1%, depending on the radiologist. The sensitivity of enhancement in the arterial-dominant phase and washout in the portal venous and/or equilibrium phases or hyperintensity on DWI was 84.4% or 85.3%, depending on the radiologist. The inter-observer agreement for the latter was very good (kappa coefficient 0.82). These results were consistent in HCCs smaller than 20mm.

CONCLUSIONS

The proposed criteria, based on the characteristics of lesions after gadolinium chelate administration and hyperintensity on DWI, significantly increased the sensitivity for the diagnosis of HCC compared to conventional criteria, regardless of tumor size.

³He lung morphometry technique: accuracy analysis and pulse sequence optimization

The (3)He lung morphometry technique (Yablonskiy et al., JAP, 2009), based on MRI measurements of hyperpolarized gas diffusion in lung airspaces, provides unique information on the lung microstructure at the alveolar level. 3D tomographic images of standard morphological parameters (mean airspace chord length, lung parenchyma surface-to-volume ratio, and the number of alveoli per unit lung volume) can be created from a rather short (several seconds) MRI scan. These parameters are most commonly used to characterize lung morphometry but were not previously available from in vivo studies. A background of the (3)He lung morphometry technique is based on a previously proposed model of lung acinar airways, treated as cylindrical passages of external radius R covered by alveolar sleeves of depth h, and on a theory of gas diffusion in these airways. The initial works approximated the acinar airways as very long cylinders, all with the same R and h. The present work aims at analyzing effects of realistic acinar airway structures, incorporating airway branching, physiological airway lengths, a physiological ratio of airway ducts and sacs, and distributions of R and h. By means of Monte-Carlo computer simulations, we demonstrate that our technique allows rather accurate measurements of geometrical and morphological parameters of acinar airways. In particular, the accuracy of determining one of the most important physiological parameter of lung parenchyma - surface-to-volume ratio - does not exceed several percent. Second, we analyze the effect of the susceptibility induced inhomogeneous magnetic field on the parameter estimate and demonstrate that this effect is rather negligible at B(0) ≤ 3T and becomes substantial only at higher B(0) Third, we theoretically derive an optimal choice of MR pulse sequence parameters, which should be used to acquire a series of diffusion-attenuated MR signals, allowing a substantial decrease in the acquisition time and improvement in accuracy of the results. It is demonstrated that the optimal choice represents three not equidistant b-values: b(1)=0, b(2)∼2 s/cm(2), b(3)∼8 s/cm(2).

Numerical simulations of short-mixing-time double-wave-vector diffusion-weighting experiments with multiple concatenations on whole-body MR systems

Double- or two-wave-vector diffusion-weighting experiments with short mixing times in which two diffusion-weighting periods are applied in direct succession, are a promising tool to estimate cell sizes in the living tissue. However, the underlying effect, a signal difference between parallel and antiparallel wave vector orientations, is considerably reduced for the long gradient pulses required on whole-body MR systems. Recently, it has been shown that multiple concatenations of the two wave vectors in a single acquisition can double the modulation amplitude if short gradient pulses are used. In this study, numerical simulations of such experiments were performed with parameters achievable with whole-body MR systems. It is shown that the theoretical model yields a good approximation of the signal behavior if an additional term describing free diffusion is included. More importantly, it is demonstrated that the shorter gradient pulses sufficient to achieve the desired diffusion weighting for multiple concatenations, increase the signal modulation considerably, e.g. by a factor of about five for five concatenations. Even at identical echo times, achieved by a shortened diffusion time, a moderate number of concatenations significantly improves the signal modulation. Thus, experiments on whole-body MR systems may benefit from multiple concatenations.

Evaluating the accuracy and precision of a two-compartment Kärger model using Monte Carlo simulations

Specific parameters of the neuronal tissue microstructure, such as axonal diameters, membrane permeability and intracellular water fractions are assessable using diffusion MRI. These parameters are commonly estimated using analytical models, which may introduce bias in the estimated parameters due to the approximations made when deriving the models. As an alternative to using analytical models, a database of signal curves generated by fast Monte Carlo simulations can be employed. Simulated diffusion MRI measurements were generated and evaluated using the two-compartment Kärger model as well as the simulation model based on a database containing signal curves from approximately 60000 simulations performed with different combinations of microstructural parameters. A protocol based on a pulsed gradient spin echo sequence with diffusion times of 30 and 60 ms and with gradient amplitudes obtainable with a clinical MRI scanner was employed for the investigations. When using the analytical model, a major negative bias (up to approximately 25%) in the estimated intracellular volume fraction was observed for short exchange times, while almost no bias was seen for the simulation model. In general, the simulation model improved the accuracy of the estimated parameters as compared to the analytical model, except for the exchange time parameter.

Double-wave-vector diffusion-weighting experiments with multiple concatenations at long mixing times

MR sequences where two diffusion-weighting periods are applied successively in a single acquisition seem to be a promising tool for the investigation of tissue structure on a microscopic level such as the characterization of the compartment size or eccentricity measures of pores. However, the application of such double-wave-vector (DWV) experiments on whole-body MR systems is hampered by the long gradient pulses required that have been shown to reduce the signal modulation. In this work, it is demonstrated that involving multiple concatenations of the two diffusion-weighting periods can ameliorate this problem in experiments with long mixing times between the two wave vectors. The recently presented tensor equation is extended to multiple concatenations. As confirmed by Monte-Carlo simulations, this model shows a good approximation of the signals observed for typical whole-body gradient pulse durations and the derived anisotropy measures are obtained with good accuracy. Most importantly, the signal modulation is increased with multiple concatenations because shorter gradient pulses can be used to achieve the desired diffusion-weighting. Thus, the multiple concatenation approach may help to improve the applicability and reliability of DWV measurements with long mixing times on standard whole-body MR systems.

About the origins of NMR diffusion-weighting induced by frequency-swept pulses

In the present work, the non-linear phase dispersion induced by slice selective frequency-swept pulses is analyzed, in order to assess NMR signal attenuation due to molecular diffusion during such pulses. In particular, theoretical considerations show that diffusion-weighting can be calculated based on the non-linear phase spatial derivative (i.e. the phase gradient), and that the phase of B(1) field at the instant of the flip does not contribute to phase scrambling and diffusion-weighting, yielding a simple analytical expressions. The theory is validated by confrontation with numerical simulations of the Bloch equations including diffusion, performed for a pair of hyperbolic secant pulses and a pair of CHIRP pulses. The simple though general conceptual framework developed here should be useful for the understanding and the exact calculation of diffusion-weighting in NMR sequences using frequency-swept pulses.

Identical, but not the same: intra-site and inter-site reproducibility of fractional anisotropy measures on two 3.0T scanners

Diffusion Tensor Imaging (DTI) is being increasingly used to assess white matter integrity and it is therefore paramount to address the test–retest reliability of DTI measures. In this study we assessed inter- and intra-site reproducibility of two nominally identical 3 T scanners at different sites in nine healthy controls using a DTI protocol representative of typical current “best practice” including cardiac gating, a multichannel head coil, parallel imaging and optimized diffusion gradient parameters. We calculated coefficients of variation (CV) and intraclass correlation coefficients (ICC) of fractional anisotropy (FA) measures for the whole brain, for three regions of interest (ROI) and for three tracts derived from these ROI by probabilistic tracking. We assessed the impact of affine, nonlinear and template based methods for spatially aligning FA maps on the reproducibility. The intra-site CV for FA ranged from 0.8% to 3.0% with ICC from 0.90 to 0.99, while the inter-site CV ranged from 1.0% to 4.1% with ICC of 0.82 to 0.99. Nonlinear image coregistration improved reproducibility compared to affine coregistration. Normalization to template space reduced the between-subject variation, resulting in lower ICC values and indicating a possibly reduced sensitivity. CV from probabilistic tractography were about 50% higher than for the corresponding seed ROI.

Reproducibility maps of the whole scan volume showed a low variation of less than 5% in the major white matter tracts but higher variations of 10–15% in gray matter regions.

One of the two scanners showed better intra-site reproducibility, while the intra-site CV for both scanners was significantly better than inter-site CV. However, when using nonlinear coregistration of FA maps, the average inter-site CV was below 2%. There was a consistent inter-site bias, FA values on site 2 were 1.0–1.5% lower than on site 1. Correction for this bias with a global scaling factor reduced the inter-site CV to the range of intra-site CV. Our results are encouraging for multi-centre DTI studies in larger populations, but also illustrate the importance of the image processing pipeline for reproducibility.

Extension of the double-wave-vector diffusion-weighting experiment to multiple concatenations

Experiments involving two diffusion-weightings in a single acquisition, so-called double- or two-wave-vector experiments, have recently been applied to measure the microscopic anisotropy in macroscopically isotropic samples or to estimate pore or compartment sizes. These informations are derived from the signal modulation observed when varying the wave vectors' orientations. However, the modulation amplitude can be small and, for short mixing times between the two diffusion-weightings, decays with increased gradient pulse lengths which hampers its detectability on whole-body MR systems. Here, an approach is investigated that involves multiple concatenations of the two diffusion-weightings in a single experiment. The theoretical framework for double-wave-vector experiments of fully restricted diffusion is adapted and the corresponding tensor approach recently presented for short mixing times extended and compared to numerical simulations. It is shown that for short mixing times (i) the extended tensor approach well describes the signal behavior observed for multiple concatenations and (ii) the relative amplitude of the signal modulation increases with the number of concatenations. Thus, the presented extension of the double-wave-vector experiment may help to improve the detectability of the signal modulations observed for short mixing times, in particular on whole-body MR systems with their limited gradient amplitudes.

3T MR imaging of postoperative recurrent middle ear cholesteatomas: value of periodically rotated overlapping parallel lines with enhanced reconstruction diffusion-weighted MR imaging

BACKGROUND AND PURPOSE

MR diagnostic of postoperative recurrent cholesteatomas is difficult. Our purpose was to compare multishot fast spin-echo periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) diffusion-weighted MR imaging (DWI) with array spatial sensitivity encoding technique (ASSET) single-shot echo-planar DWI and late postgadolinium T1-weighted MR imaging for the detection of postoperative recurrent middle ear cholesteatomas with a 3T imaging unit.

MATERIALS AND METHODS

Thirty-five patients with suggested postoperative recurrent middle ear cholesteatoma underwent 3T MR imaging with PROPELLER DWI, ASSET echo-planar DWI, and late postgadolinium T1-weighted MR imaging. Three radiologists (2 seniors, 1 fellow) analyzed unlabeled images for visualization of recurrence. Interobserver and intraobserver agreement was assessed by using the Cohen kappa statistic test. Sensitivity, specificity, and predictive value were assessed for the 3 observers.

RESULTS

Nineteen recurrent cholesteatomas were diagnosed. PROPELLER interobserver agreement was very good (1, 0.89, 0.89) among the 3 observers. Intraobserver agreement between PROPELLER and T1-weighted imaging was very good to moderate (0.88, 0.57, 0.58). PROPELLER DWI provided less interobserver variability than other sequences, and the best sensitivity, specificity, and predictive value.

CONCLUSIONS

On a 3T imaging unit, multishot fast spin-echo PROPELLER DWI allows an easier detection of postoperative recurrent middle ear cholesteatoma than T1-weighted imaging by reducing artifacts and by its better contrast. DWI with PROPELLER is diagnostically robust and accurate.

A geometric flow-based approach for diffusion tensor image segmentation

Diffusion tensor magnetic resonance imaging (DT-MRI, shortened as DTI) produces, from a set of diffusion-weighted magnetic resonance images, tensor-valued images where each voxel is assigned a 3x3 symmetric, positive-definite matrix. This tensor is simply the covariance matrix of a local Gaussian process with zero mean, modelling the average motion of water molecules. We propose a three-dimensional geometric flow-based model to segment the main core of cerebral white matter fibre tracts from DTI. The segmentation is carried out with a front propagation algorithm. The front is a three-dimensional surface that evolves along its normal direction with speed that is proportional to a linear combination of two measures: a similarity measure and a consistency measure. The similarity measure computes the similarity of the diffusion tensors at a voxel and its neighbouring voxels along the normal to the front; the consistency measure is able to speed up the propagation at locations where the evolving front is more consistent with the diffusion tensor field, to remove noise effect to some extent, and thus to improve results. We validate the proposed model and compare it with some other methods using synthetic and human brain DTI data; experimental results indicate that the proposed model improves the accuracy and efficiency in segmentation.

Altered cingulate white matter connectivity in panic disorder patients

OBJECTIVE

Functional imaging studies of panic disorder subjects suggest an increased activation of the cingulate regions of the brain. Aim of the current study was to explore the white matter connectivity differences between subjects with panic disorder and healthy comparison subjects.

METHOD

Structural white matter connectivity, as determined from fractional anisotropy (FA) values obtained by diffusion tensor imaging, was assessed for anterior and posterior cingulate regions in 24 panic disorder patients and 24 age and sex-matched healthy comparison subjects.

RESULTS

Subjects with panic disorder exhibited significantly greater FA values in left anterior and right posterior cingulate regions (by 13.3% and 19.6%, respectively) relative to comparison subjects. White matter connectivity for these two cingulate regions was also positively correlated with clinical severity, as determined by Panic Disorder Severity Scale. FA values in left anterior cingulate region negatively correlated with the time of Trail Making Tests and positively with Digit Symbol Substitution Test.

CONCLUSIONS

Findings suggest a potential 'enhancement' in white matter connectivity in left anterior and right posterior cingulate regions in panic disorder, and that these changes may play an important role in mediating clinical symptoms of panic disorder.

Altered resting-state functional connectivity and anatomical connectivity of hippocampus in schizophrenia

Hippocampus has been implicated in participating in the pathophysiology of schizophrenia. However, the functional and anatomical connectivities between hippocampus and other regions are rarely concurrently investigated in schizophrenia. In the present study, both functional magnetic resonance imaging (fMRI) during rest and diffusion tensor imaging (DTI) were performed on 17 patients with paranoid schizophrenia and 14 healthy subjects. Resting-state functional connectivities of the bilateral hippocampi were separately analyzed by selecting the anterior hippocampus as region of interest. The fornix body was reconstructed by diffusion tensor tractography, and the integrity of this tract was evaluated using fractional anisotropy (FA). In patients with schizophrenia, the bilateral hippocampi showed reduced functional connectivities to some regions which have been reported to be involved in episodic memory, such as posterior cingulate cortex, extrastriate cortex, medial prefrontal cortex, and parahippocampus gyrus. We speculated that these reduced connectivity may reflect the disconnectivity within a neural network related to the anterior hippocampus in schizophrenia. Meanwhile the mean FA of the fornix body was significantly reduced in patients, indicating the damage in the hippocampal anatomical connectivity in schizophrenia. The concurrence of the functional disconnectivity and damaged anatomical connectivity between the hippocampus and other regions in schizophrenia suggest that the functional-anatomical relationship need to be further investigated.

Diffusion-based magnetic resonance imaging and tractography in epilepsy

Diffusion-based imaging is an advanced MRI technique that is sensitive to the movement of water molecules, providing additional information on the micro-structural arrangement of tissue. Qualitative and quantitative analysis of peri, post and interictal diffusion images can aid the localization of seizure foci. Diffusion tensor tractography is an extension of diffusion-based imaging, and can provide additional information about white matter pathways. Both techniques are able to increase understanding of the effects of epilepsy on the structural organization of the brain, and can be used to optimize presurgical planning of patients with epilepsy. This review focuses on the basis, applications, limitations, and future directions of diffusion imaging in epilepsy. Literature search strategy: We searched Pubmed using the terms "diffusion MRI or diffusion tensor MRI or tractography and epilepsy."

K-space and image space combination for motion artifact correction in multicoil multishot diffusion weighted imaging

Motion during diffusion encodings leads to phase errors in different shots of a multishot acquisition. Phase differences in k-space data among shots result in phase cancellation artifacts in the reconstructed image. Due to aliasing of the phase from under-sampled regions of the shot, correction of the phase error using direct low-resolution phase subtraction is incomplete. We introduce a new k-space and image-space combination (KICT) method for motion artifacts cancellation that avoids incomplete phase error correction. Further, the method preserves the phase of the object, which is important for parallel imaging applications.