Diffusion-weighted Imaging MRI Research Articles

Neuroimaging in infants with congenital cytomegalovirus infection and its correlation with outcome: emphasis on white matter abnormalities

ObjectiveTo evaluate the association between neuroimaging and outcome in infants with congenital cytomegalovirus (cCMV), focusing on qualitative MRI and quantitative diffusion-weighted imaging of white matter abnormalities (WMAs).MethodsMulticentre retrospective cohort study...

Restriction spectrum imaging with elastic image registration for automated evaluation of response to neoadjuvant therapy in breast cancer.

Dynamic contrast-enhanced MRI (DCE) and apparent diffusion coefficient (ADC) are currently used to evaluate treatment response of breast cancer. The purpose of the current study was to evaluate the three-component Restriction Spectrum Imaging model (RSI3C), a recent diffusion-weighted MRI (DWI)-based tumor classification method, combined with elastic image registration, to automatically monitor breast tumor size throughout neoadjuvant therapy. Breast cancer patients (n=27) underwent multi-parametric 3T MRI at four time points during treatment. Elastically-registered DWI images were used to generate an automatic RSI3C response classifier, assessed against manual DCE tumor size measurements and mean ADC values. Predictions of therapy response during treatment and residual tumor post-treatment were assessed using non-pathological complete response (non-pCR) as an endpoint. Ten patients experienced pCR. Prediction of non-pCR using ROC AUC (95% CI) for change in measured tumor size from pre-treatment time point to early-treatment time point was 0.65 (0.38-0.92) for the RSI3C classifier, 0.64 (0.36-0.91) for DCE, and 0.45 (0.16-0.75) for change in mean ADC. Sensitivity for detection of residual disease post-treatment was 0.71 (0.44-0.90) for the RSI3C classifier, compared to 0.88 (0.64-0.99) for DCE and 0.76 (0.50-0.93) for ADC. Specificity was 0.90 (0.56-1.00) for the RSI3C classifier, 0.70 (0.35-0.93) for DCE, and 0.50 (0.19-0.81) for ADC. The automatic RSI3C classifier with elastic image registration suggested prediction of response to treatment after only three weeks, and showed performance comparable to DCE for assessment of residual tumor post-therapy. RSI3C may guide clinical decision-making and enable tailored treatment regimens and cost-efficient evaluation of neoadjuvant therapy of breast cancer.

Using MRI appendicitis scale and DWI for the diagnosis of acute appendicitis in pregnant women.

To assess the performance of MRI scale for the diagnosis of acute appendicitis in pregnant women and to determine the added diagnostic value of diffusion-weighted imaging (DWI). From January 2018 to December 2020, 80 patients were included. All MRI were performed with a 1.5-Tesla scanner with anterior array body coil. This analysis included (1) T2-weighted imaging (T2WI), (2) fat-saturated T2WI, and (3) DWI. Two radiologists blinded to the diagnosis recorded their assessment of four findings: appendiceal diameter, appendiceal wall thickness, luminal mucus, and periappendiceal inflammation. The MRI scale of acute appendicitis which ranged from 0 to 4 was determined from these factors. An additional one point was added to the MRI appendicitis scale in those patients with evidence of appendiceal restricted diffusion on DWI. The diagnostic values and predictive factors were computed. Multivariate analysis demonstrated that the calculated MRI appendicitis scale was a significant independent predictor of acute appendicitis with a sensitivity of 96.6%, specificity of 90.2%, and PPV of 84.8%. The odds ratio of appendicitis is increased by 22.3 times for every increase in one point on the MRI appendicitis scale. Therefore, the addition of one point for restricted diffusion in the appendix on DWI imaging can add substantial value, both positive and negative predictive value, towards making an accurate diagnosis of acute appendicitis. MRI appendicitis scale is an objective and significant independent predictive factor for acute appendicitis in pregnant women. Incorporation of diffusion weighted imaging to MRI can improve diagnosis of acute appendicitis. MRI appendicitis scale is an objective and significant independent predictor of acute appendicitis in pregnant women. Incorporation of DWI/ADC map to MRI examinations can improve diagnosis of acute appendicitis in pregnant women. • MRI appendicitis scale is an objective and significant independent predictive factor for acute appendicitis in pregnant women. • The odds ratio of appendicitis can be increased by 22.3 times for every increase of one unit in MRI scale. • Incorporation of diffusion-weighted imaging to MRI examinations can add value to the scale (4.2 ± 0.7 vs. 0.7 ± 1.1; p < 0.001) among pregnant women with appendicitis versus pregnant women without appendicitis.

677 Amide Proton Transfer-Weighted Imaging Versus Diffusion-Weighted Imaging for Monitoring Treatment Response in Glioma Patients: A Systematic Review and Meta-Analysis

Abstract Aim Monitoring treatment response in glioma (GM) patients remains a challenge, as tumour recurrence (TR) and treatment-related injury (TRI) both appear similarly on standard magnetic resonance imaging (MRI). Although diffusion-weighted MRI (DWI) is gold standard, equivocal patients still undergo invasive biopsies for diagnosis. Amide proton transfer-weighted MRI (APTw) may more accurately differentiate TR from TRI, reducing surgical intervention rates. Hence, this systematic review and meta-analysis aimed to determine how APTw compares to DWI in the identification of TR from TRI. Method A search strategy was used to select studies investigating the diagnostic ability of DWI or APTw in detecting TR from Ovid MEDLINE ®, Ovid Embase, Web of Science, Cochrane Central Register of Controlled Trials, and Thai Clinical Trials Registry. Selection criteria were applied to retrieve studies and methodologies critically appraised according to the QUADAS-2 tool. Conclusions from studies were synthesised, and the sensitivity and specificity for TR detection pooled. Results 18 studies were included in the analysis (11 DWI, 6 APTw, 1 both). For TR, APTw signal measured significantly higher, whereas apparent diffusion coefficients derived from DWI images were significantly lower. In DWI studies, combined sensitivity and specificity for TR was 84.4% (95% CI, 72.5%-91.7%) and 81.2% (95% CI, 67.9%-89.8%) accordingly. Meta-analysis was not performed for APTw due to limited study numbers. In general, studies had low methodological quality and were associated with a risk of bias. Conclusions Overall, though comparisons between DWI and APTw in monitoring GM treatment were inconclusive, this study supports the potential use of APTw in neurosurgery.

Comparative evaluation of brain perfusion with ASL and DSC MRI following intracranial vascular flow diverter stent replacement.

The objective of this study was to asses brain perfusion parameters and ischemic changes following treatment of aneurysm with flow diverters with two different perfusion MRI technique (Arterial spin labeling and DSC MRI), and to compare the results and effectiveness of these two methods. The prospective data was collected from patients with aneurysm who treated with flow diverters. MR examinations, including diffusion-weighted imaging (DWI), ASL, and DSC perfusion MRI, were conducted before and after treatment within the first week and at 6 months. Perfusion parameters of territory area and contralateral side were measured and analyzed by statistically. The relationships between ASL and DSC parameters were analyzed by using Sperman's correlation analysis. A total of 14 cases of aneurysms in 11 patients treated successfully with endovascular flow diverter stent placement. Pretreatment and post treatment (within first week and 6 months) MRI images were evaluated. Asymptomatic randomly distributed millimetric restricted diffusion foci were observed in 8 of all patients. There was no statistically difference between pre and post treatment perfusion parameters (p > 0.05). A statistically significant correlation was found between variable ASL CBF, and the variables of DSC CBF and TTP. Notwithstanding the fact that flow diverters change flow dynamics in aneurysm sac, there is no any perfusion abnormality in the territory area. Asymptomatic randomly distributed diffusion restricted foci in the both cerebral hemisphere can be observed. ASL and DSC MRI are effective for evaluation of brain perfusion.

Radiomic signatures from T2W and DWI MRI are predictive of tumour hypoxia in colorectal liver metastases

BackgroundTumour hypoxia is a negative predictive and prognostic biomarker in colorectal cancer typically assessed by invasive sampling methods, which suffer from many shortcomings. This retrospective proof-of-principle study explores the potential of MRI-derived imaging markers in predicting tumour hypoxia non-invasively in patients with colorectal liver metastases (CLM).MethodsA single-centre cohort of 146 CLMs from 112 patients were segmented on preoperative T2-weighted (T2W) images and diffusion-weighted imaging (DWI). HIF-1 alpha immunohistochemical staining index (high/low) was used as a reference standard. Radiomic features were extracted, and machine learning approaches were implemented to predict the degree of histopathological tumour hypoxia.ResultsRadiomic signatures from DWI b200 (AUC = 0.79, 95% CI 0.61–0.93, p = 0.002) and ADC (AUC = 0.72, 95% CI 0.50–0.90, p = 0.019) were significantly predictive of tumour hypoxia. Morphological T2W TE75 (AUC = 0.64, 95% CI 0.42–0.82, p = 0.092) and functional DWI b0 (AUC = 0.66, 95% CI 0.46–0.84, p = 0.069) and b800 (AUC = 0.64, 95% CI 0.44–0.82, p = 0.071) images also provided predictive information. T2W TE300 (AUC = 0.57, 95% CI 0.33–0.78, p = 0.312) and b = 10 (AUC = 0.53, 95% CI 0.33–0.74, p = 0.415) images were not predictive of tumour hypoxia.ConclusionsT2W and DWI sequences encode information predictive of tumour hypoxia. Prospective multicentre studies could help develop and validate robust non-invasive hypoxia-detection algorithms.Critical relevance statementHypoxia is a negative prognostic biomarker in colorectal cancer. Hypoxia is usually assessed by invasive sampling methods. This proof-of-principle retrospective study explores the role of AI-based MRI-derived imaging biomarkers in non-invasively predicting tumour hypoxia in patients with colorectal liver metastases (CLM).Graphical

Immune checkpoint inhibitor treatment of brain metastasis associated with a less invasive growth pattern, higher T-cell infiltration and raised tumor ADC on diffusion weighted MRI

BackgroundBrain metastases are the most common intracranial tumors with an increasing incidence. They are an important cause of morbidity and mortality in patients with solid organ cancer and a focus of recent clinical research and experimental interest. Immune checkpoint inhibitors are being increasingly used to treat solid organ cancers.MethodsTo determine whether immune checkpoint inhibitors were biologically effective in the brain, we compared melanoma brain metastasis samples where treatment with ipilimumab had occurred preoperatively to those who had not received any immune modulating therapy and looked for histopathological (invasion, vascularity, metastasis inducing proteins, matrix metalloproteinases, immune cell infiltration, tissue architecture) and advanced MRI differences (diffusion weighted imaging).ResultsCo-localized tissue samples from the same regions as MRI regions of interest showed significantly lower vascularity (density of CD34 + vessels) in the core and higher T-cell infiltration (CD3 + cells) in the leading edge for ipilimumab-treated brain metastasis samples than for untreated cases and this correlated with a higher tumor ADC signal at post-treatment/preoperative MRI brain.ConclusionsTreatment of a melanoma brain metastasis with ipilimumab appears to cause measurable biological changes in the tumor that can be correlated with post-treatment diffusion weighted MRI imaging, suggesting both a mechanism of action and a possible surrogate marker of efficacy.

Changes in serial multiparametric MRI and FDG-PET/CT functional imaging during radiation therapy can predict treatment response in patients with head and neck cancer

ObjectivesTo test if tumour changes measured using combination of diffusion-weighted imaging (DWI) MRI and FDG-PET/CT performed serially during radiotherapy (RT) in mucosal head and neck carcinoma can predict treatment response.MethodsFifty-five patients from two prospective imaging biomarker studies were analysed. FDG-PET/CT was performed at baseline, during RT (week 3), and post RT (3 months). DWI was performed at baseline, during RT (weeks 2, 3, 5, 6), and post RT (1 and 3 months). The ADCmean from DWI and FDG-PET parameters SUVmax, SUVmean, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were measured. Absolute and relative change (%∆) in DWI and PET parameters were correlated to 1-year local recurrence. Patients were categorised into favourable, mixed, and unfavourable imaging response using optimal cut-off (OC) values of DWI and FDG-PET parameters and correlated to local control.ResultsThe 1-year local, regional, and distant recurrence rates were 18.2% (10/55), 7.3% (4/55), and 12.7% (7/55), respectively. ∆Week 3 ADCmean (AUC 0.825, p = 0.003; OC ∆ > 24.4%) and ∆MTV (AUC 0.833, p = 0.001; OC ∆ > 50.4%) were the best predictors of local recurrence. Week 3 was the optimal time point for assessing DWI imaging response. Using a combination of ∆ADCmean and ∆MTV improved the strength of correlation to local recurrence (p ≤ 0.001). In patients who underwent both week 3 MRI and FDG-PET/CT, significant differences in local recurrence rates were seen between patients with favourable (0%), mixed (17%), and unfavourable (78%) combined imaging response.ConclusionsChanges in mid-treatment DWI and FDG-PET/CT imaging can predict treatment response and could be utilised in the design of future adaptive clinical trials.Clinical relevance statementOur study shows the complementary information provided by two functional imaging modalities for mid-treatment response prediction in patients with head and neck cancer.Key Points•FDG-PET/CT and DWI MRI changes in tumour during radiotherapy in head and neck cancer can predict treatment response.•Combination of FDG-PET/CT and DWI parameters improved correlation to clinical outcome.•Week 3 was the optimal time point for DWI MRI imaging response assessment.

Diagnostic value of whole -body diffusion weighted imaging added to bone scan in early diagnosis of bone metastases in breast cancer patients

BackgroundMetastases to the bones are a frequent location of metastasis in advanced breast cancer and are responsible for substantial morbidity and healthcare expenses. Imaging has been crucial in directing patient therapy for decades, contributing to the staging and response evaluation of the skeleton. This research aimed to assess the diagnostic value of whole-body magnetic resonance imaging with diffusion-weighted imaging added to radionuclide bone scans for early diagnosis of bone metastases in breast cancer patients.ResultsThe study was a prospective observational cohort study performed on 20 patients with breast cancer and suspected bone metastases. The patients were evaluated first by obtaining a detailed personal history. Laboratory tests, including CBC, liver, and kidney function tests were assessed. All patients were examined by diffusion-weighted whole-body MRI (DWIBS; diffusion-weighted imaging with background body signal suppression) images and bone scintigraphy after intravenous injection of 20 mci of technetium-99m (99mTc) methylene diphosphonate using a dual head gamma camera. The total number of lesions detected by bone scan was 74, and 75 lesions were seen by DWIBS. Twenty-four lesions were missed by bone scan and detected by DWIBS. Fourteen lesions were detected by bone scan and found free by DWIBS examination in the spine and pelvic bones.ConclusionsWhole body DWIBS seems to be a promising method of imaging in detecting bone metastases from breast cancer that could be used complementary to the traditional bone scan for more accurate diagnosis and staging of the tumor, helping to determine the most appropriate protocol of management.

Differentiation of placenta percreta through MRI features and diffusion-weighted magnetic resonance imaging

ObjectivesTo identify whether parameters measured from diffusion kurtosis and intravoxel incoherent motion help diagnose placenta percreta.MethodsWe retrospectively enrolled 75 patients with PAS disorders including 13 patients with placenta percreta and 40 patients without PAS disorders. Each patients underwent diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI). The apparent diffusion coefficient (ADC), perfusion fraction (f), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), mean diffusion kurtosis (MK) and mean diffusion coefficient (MD) were measured by the volumetric analysis and compared. MRI features were also analyzed and compared. The receiver operating characteristic (ROC) curve and logistic regression analysis were used to evaluate the diagnostic efficiency of different diffusion parameters and MRI features for distinguishing placental percreta.ResultsD* was an independent risk factor from DWI for predicting placenta percreta with sensitivity of 73% and specificity of 76%. Focal exophytic mass remained as independent risk factor from MRI features for predicting placenta percreta with sensitivity of 72.7% and specificity of 88.1%. When the two risk factors were combined together, the AUC was the highest, 0.880 (95% CI 0.8–0.96).ConclusionD* and focal exophytic mass were associated with placenta percreta. A combination of the 2 risk factors can be used to predict placenta percreta.Critical relevance statementA combination of D* and focal exophytic mass can be used to differentiate placenta percreta.

Evaluation of renal cold ischemia-reperfusion injury with intravoxel incoherent motion diffusion-weighted imaging and blood oxygenation level-dependent MRI in a rat model.

Purpose: Cold ischemia-reperfusion injury (CIRI) is one of the most serious complications following renal transplantation. The current study investigated the feasibility of Intravoxel Incoherent Motion (IVIM) imaging and blood oxygenation level-dependent (BOLD) in the evaluation of different degrees of renal cold ischemia-reperfusion injury in a rat model. Methods: Seventy five rats were randomly divided into three groups (N = 25 for each group): T0: sham-operated group, T2/T4: CIRI groups with different cold ischemia hours (2, 4h, respectively). The rat model of CIRI group was established by left kidney cold ischemia with right nephrectomy. All the rats received a baseline MRI before the surgery. Five rats in each group were randomly selected to undergo an MRI examination at 1h, day 1, day 2 and day 5 after CIRI. The IVIM and BOLD parameters were studied in the renal cortex (CO), the outer stripe of the outer medulla (OSOM), and the inner stripe of the outer medulla (ISOM) followed by histological analysis to examine Paller scores, peritubular capillary (PTC) density, apoptosis rate and biochemical indicators to obtain the contents of serum creatinine (Scr), blood urea nitrogen (BUN), superoxide dismutase (SOD) and malondialdehyde (MDA). Results: The D, D*, PF and T2* values in the CIRI groups were lower than those in the sham-operated group at all timepoints (all p < 0.05). The prolonged cold ischemia times resulted in gradually lower D, D*, PF and T2* values (all p < 0.05). The D and T2* values of cortex and OSOM in Group T0 and T2 returned to the baseline level (all p > 0.05) except Group T4. The D* and PF values of cortex, OSOM and ISOM in Group T2 and T4 still remained below the normal levels (all p < 0.05) except Group T0. D, D*, PF and T2* values were strongly correlated with histopathological (Paller scores, PTC density and apoptosis rate) and the biochemistry indicators (SOD and MDA) (|r|>0.6, p < 0.001). D*, PF and T2* values were moderately to poorly correlated with some biochemistry indicators (Scr and BUN) (|r|<0.5, p < 0.05). Conclusion: IVIM and BOLD can serve as noninvasive radiologic markers for monitoring different degrees of renal impairment and recovery after renal CIRI.

P188 Measurement of response to treatment in axial spondyloarthritis using quantitative imaging biomarkers: a prospective observational cohort study

Abstract Background/Aims Objective assessments of disease activity and response to treatment in axial spondyloarthritis (axSpA) remain a challenge. Diffusion-weighted magnetic resonance imaging (DW-MRI) and chemical shift-encoded MRI (CSE-MRI) inform on bone marrow oedema and fat content and could provide more accurate assessments of disease activity and therapeutic response. This study aims to determine the responsiveness and validity of quantitative imaging biomarkers (QIBs) obtained from DW-MRI and CSE-MRI using the partially-automated Bone Edema and Adiposity Characterisation with Histograms (BEACH) tool in patients with axial spondyloarthritis undergoing biologic therapy. Methods Conventional MRI, DWI and CSI was performed on 30 patients with active axSpA at baseline and after 12 - 16 weeks of biologic treatment. Apparent diffusion coefficient (ADC) and proton density fat fraction (PDFF) measures were analysed using the BEACH tool. Conventional MR images were assessed using established visual scoring methods. QIBs were assessed in terms of change after treatment and correlation with clinical and conventional MRI measures of disease activity. Results There were significant reductions for ADC values, while PDFF-scores showed nonsignificant reductions. Responsiveness to therapy was moderate for ADC measures and comparable to established visual scoring methods for bone marrow oedema. ADC and PDFF correlated well with conventional bone marrow oedema and fatty change scores respectively. Inter-observer variability was lower for QIBs compared with conventional visual scores methods. Conclusion ADC measures are sensitive to changes in inflammation in axSpA following biologic therapy and show promise as a biomarker of disease activity in axSpA. Disclosure A. Jones: None. T.J.P. Bray: None. N. Sakai: None. A. Bainbridge: None. C. Ciurtin: None. M.A. Hall-Craggs: None.

Role of Diffusion MRI in Characterizing Benign and Malignant Breast Lesions

Background: Diffusion-weighted MRI imaging (DWI) is frequently employed, particularly to assess organs such as breast, prostate, ovaries, liver, and pancreas. Aim: The present study aimed to assess the diffusion MRI role in characterization benign breast lesions from malignant breast lesions. Patients and Methods: This prospective study was conducted on 260 breasts lesions of 200 patients in the Department of Radiology, Jinnah Hospital Lahore and DHQ Hospital, Vihari from January 2021 to September 2022. Females (15 and 75 years) with breast lesion of diameter (&gt;1cm) were enrolled. About 60 patients underwent breast MRI with contrast and DWI. The remaining 140 patients underwent DWI came for sonomammography. ADC values (b-vale 0-300, 0-600, and 0-1000) for all lesions were computed for differentiating the benign and malignant lesions. Benign and malignant breast lesions were categorized based on ADC values (1.3-1.5 mm2/s) and (0.85-1.1 mm2/s) respectively. Results: Of the total 260 breast lesions, the incidence of benign and malignant breast lesions based on ADC values were 192 (73.8%) and 68 (22.2%) respectively. About 4 lesions were benign based on ADC value but were proven malignant after intervention. This approach of detecting malignant lesions based on ADC values has a specificity 100%, sensitivity 97.22%, positive prediction value 100%, and negative prediction value 99%. The ADC value of benign versus malignant breast lesions at b-value (0-300), (0-600), and (0-1000) were 1.56±0.23 vs. 0.82±0.21, 1.54±0.09 vs. 0.89±0.17, and 1.52±0.16 vs. 0.84±0.18 respectively. Conclusion: The present study demonstrated that DWI for breast lesions had a good sensitivity and specificity for distinguishing benign from malignant lesions. Keywords: Breast lesions, DWI, MRI, benign lesions, malignant lesions

Incidence, Clinical Significance, and Longitudinal Signal Characteristics of Ischemic Lesions Related to Diagnostic Cerebral Catheter Angiography

PurposeCerebral DSA is a routine procedure with few complications. However, it is associated with presumably clinically inapparent lesions detectable on diffusion-weighted MRI imaging (DWI lesions). However, there are insufficient data regarding incidence, etiology, clinical relevance, and longitudinal development of these lesions. This study prospectively evaluated subjects undergoing elective diagnostic cerebral DSA for the occurrence of DWI lesions, potentially associated clinical symptoms and risk factors, and longitudinally monitored the lesions using state-of-the-art MRI.Materials and MethodsEighty-two subjects were examined by high-resolution MRI within 24 h after elective diagnostic DSA and lesion occurrence was qualitatively and quantitatively evaluated. Subjects’ neurological status was assessed before and after DSA by clinical neurological examination and a perceived deficit questionnaire. Patient-related risk factors and procedural DSA data were documented. Subjects with lesions received a follow-up MRI and were questioned for neurological deficits after a median of 5.1 months.ResultsAfter DSA, 23(28%) subjects had a total of 54 DWI lesions. Significantly associated risk factors were number of vessels probed, intervention time, age, arterial hypertension, visible calcified plaques, and less examiner experience. Twenty percent of baseline lesions converted to persistent FLAIR lesions at follow-up. After DSA, none of the subjects had a clinically apparent neurological deficit. Self-perceived deficits were nonsignificantly higher at follow-up.ConclusionCerebral DSA is associated with a considerable number of postinterventional lesions, some persisting as scars in brain tissue. Presumably because of the small lesion size and inconsistent location, no clinically apparent neurological deficits have been observed. However, subtle self-perceived changes may occur. Therefore, special attention is needed to minimize avoidable risk factors.

RU-Net: skull stripping in rat brain MR images after ischemic stroke with rat U-Net

BackgroundExperimental ischemic stroke models play a fundamental role in interpreting the mechanism of cerebral ischemia and appraising the development of pathological extent. An accurate and automatic skull stripping tool for rat brain image volumes with magnetic resonance imaging (MRI) are crucial in experimental stroke analysis. Due to the deficiency of reliable rat brain segmentation methods and motivated by the demand for preclinical studies, this paper develops a new skull stripping algorithm to extract the rat brain region in MR images after stroke, which is named Rat U-Net (RU-Net).MethodsBased on a U-shape like deep learning architecture, the proposed framework integrates batch normalization with the residual network to achieve efficient end-to-end segmentation. A pooling index transmission mechanism between the encoder and decoder is exploited to reinforce the spatial correlation. Two different modalities of diffusion-weighted imaging (DWI) and T2-weighted MRI (T2WI) corresponding to two in-house datasets with each consisting of 55 subjects were employed to evaluate the performance of the proposed RU-Net.ResultsExtensive experiments indicated great segmentation accuracy across diversified rat brain MR images. It was suggested that our rat skull stripping network outperformed several state-of-the-art methods and achieved the highest average Dice scores of 98.04% (p < 0.001) and 97.67% (p < 0.001) in the DWI and T2WI image datasets, respectively.ConclusionThe proposed RU-Net is believed to be potential for advancing preclinical stroke investigation and providing an efficient tool for pathological rat brain image extraction, where accurate segmentation of the rat brain region is fundamental.

Efficient approximate signal reconstruction for correction of gradient nonlinearities in diffusion-weighted imaging

In diffusion weighted MRI (DW-MRI), hardware nonlinearities lead to spatial variations in the orientation and magnitude of diffusion weighting. While the correction of these spatial distortions has been well established for analyses of DW-MRI, the existing voxel-wise empirical correction for gradient nonlinearities requires reimplementation of existing models, as the resultant gradients vary by voxel. Herein, we propose a two-step signal approximation after voxel-wise correction of gradient nonlinearity effects in DW-MRI. The proposed technique (1) scales the diffusion signal and (2) resamples the gradient orientations. This results in uniform gradients across the corrected image and provides the key advantage of seamless integration into current diffusion workflows. We investigated the validity of our technique by fitting a multi-compartment neurite orientation dispersion and density imaging (NODDI) model to the empirical correction and proposed approximation in five subjects from the MASiVar pediatric dataset. We evaluated intra-cellular volume fraction (iVF), CSF volume fraction (cVF), and orientation dispersion index (ODI) from NODDI. The Cohen's d of iVF, cVF and ODI between the techniques was <0.2 indicating the proposed technique does not exhibit significant differences from the voxel-wise correction technique. Our two-step signal approximation is an efficient representation of the voxel-wise gradient table correction. Using this approximation, correction of gradient nonlinearities can be easily incorporated into existing diffusion preprocessing pipelines and is implemented in “PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images”.

Association of cortical and subcortical microstructure with disease severity: impact on cognitive decline and language impairments in frontotemporal lobar degeneration

BackgroundCortical and subcortical microstructural modifications are critical to understanding the pathogenic changes in frontotemporal lobar degeneration (FTLD) subtypes. In this study, we investigated cortical and subcortical microstructure underlying cognitive and language impairments across behavioral variant of frontotemporal dementia (bvFTD), semantic variant of primary progressive aphasia (svPPA), and nonfluent variant of primary progressive aphasia (nfvPPA) subtypes.MethodsThe current study characterized 170 individuals with 3 T MRI structural and diffusion-weighted imaging sequences as portion of the Frontotemporal Lobar Degeneration Neuroimaging Initiative study: 41 bvFTD, 35 nfvPPA, 34 svPPA, and 60 age-matched cognitively unimpaired controls. To determine the severity of the disease, clinical dementia rating plus national Alzheimer’s coordinating center behavior and language domains sum of boxes scores were used; other clinical measures, including the Boston naming test and verbal fluency test, were also evaluated. We computed surface-based cortical thickness and cortical and subcortical microstructural metrics using tract-based spatial statistics and explored their relationships with clinical and cognitive assessments.ResultsCompared with controls, those with FTLD showed substantial cortical mean diffusivity alterations extending outside the regions with cortical thinning. Tract-based spatial statistics revealed that anomalies in subcortical white matter diffusion were widely distributed across the frontotemporal and parietal areas. Patients with bvFTD, nfvPPA, and svPPA exhibited distinct patterns of cortical and subcortical microstructural abnormalities, which appeared to correlate with disease severity, and separate dimensions of language functions.ConclusionsOur findings imply that cortical and subcortical microstructures may serve as sensitive biomarkers for the investigation of neurodegeneration-associated microstructural alterations in FTLD subtypes.Graphical Flowchart of the study design (see materials and methods for detailed description).

Whole-body diffusion magnetic resonance imaging with simultaneous multi-slice excitation in children and adolescents

BackgroundWhole-body magnetic resonance imaging (WB-MRI) is an increasingly used guideline-based imaging modality for oncological and non-oncological pathologies during childhood and adolescence. While diffusion-weighted imaging (DWI), a part of WB-MRI, enhances image interpretation and improves sensitivity, it also requires the longest acquisition time during a typical WB-MRI scan protocol. Interleaved short tau inversion recovery (STIR) DWI with simultaneous multi-slice (SMS) acquisition is an effective way to speed up examinations.ObjectiveIn this study of children and adolescents, we compared the acquisition time, image quality, signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) values of an interleaved STIR SMS-DWI sequence with a standard non-accelerated DWI sequence for WB-MRI.Materials and methodsTwenty children and adolescents (mean age: 13.9 years) who received two WB-MRI scans at a maximum interval of 18 months, consisting of either standard DWI or SMS-DWI MRI, respectively, were included. For quantitative evaluation, the signal-to-noise ratio (SNR) was determined for b800 images and ADC maps of seven anatomical regions. Image quality evaluation was independently performed by two experienced paediatric radiologists using a 5-point Likert scale. The measurement time per slice stack, pause between measurements including shim and total measurement time of DWI for standard DWI and SMS-DWI were extracted directly from the scan data.ResultsWhen including the shim duration, the acquisition time for SMS-DWI was 43% faster than for standard DWI. Qualitatively, the scores of SMS-DWI were higher in six locations in the b800 images and four locations in the ADC maps. There was substantial agreement between both readers, with a Cohen’s kappa of 0.75. Quantitatively, the SNR in the b800 images and the ADC maps did not differ significantly from one another.ConclusionWhole body-MRI with SMS-DWI provided equivalent image quality and reduced the acquisition time almost by half compared to the standard WB-DWI protocol.

Chronic exposure to inhaled vaporized cannabis high in Δ9-THC alters brain structure in adult female mice.

The medical and recreational use of cannabis has increased in the United States. Its chronic use can have detrimental effects on the neurobiology of the brain-effects that are age-dependent. This was an exploratory study looking at the effects of chronically inhaled vaporized cannabis on brain structure in adult female mice. Adult mice were exposed daily to vaporized cannabis (10.3% THC and 0.05% CBD) or placebo for 21 days. Following cessation of treatment mice were examined for changes in brain structure using voxel-based morphometry and diffusion weighted imaging MRI. Data from each imaging modality were registered to a 3D mouse MRI atlas with 139 brain areas. Mice showed volumetric changes in the forebrain particularly the prefrontal cortex, accumbens, ventral pallidum, and limbic cortex. Many of these same brain areas showed changes in water diffusivity suggesting alterations in gray matter microarchitecture. These data are consistent with much of the clinical findings on cannabis use disorder. The sensitivity of the dopaminergic system to the daily exposure of vaporized cannabis raises concerns for abuse liability in drug naïve adult females that initiate chronic cannabis use.

Amide Proton Transfer-Weighted Imaging Combined with ZOOMit Diffusion Kurtosis Imaging in Predicting Lymph Node Metastasis of Cervical Cancer

The aim of this study is to investigate the feasibility of amide proton transfer-weighted (APTw) imaging combined with ZOOMit diffusion kurtosis imaging (DKI) in predicting lymph node metastasis (LNM) in cervical cancer (CC). Sixty-one participants with pathologically confirmed CC were included in this retrospective study. The APTw MRI and ZOOMit diffusion-weighted imaging (DWI) were acquired. The mean values of APTw and DKI parameters including mean kurtosis (MK) and mean diffusivity (MD) of the primary tumors were calculated. The parameters were compared between the LNM and non-LNM groups using the Student's t-test or Mann-Whitney U test. Binary logistic regression analysis was performed to determine the association between the LNM status and the risk factors. The diagnostic performance of these quantitative parameters and their combinations for predicting the LNM was assessed with receiver operating characteristic (ROC) curve analysis. Patients were divided into the LNM group (n = 17) and the non-LNM group (n = 44). The LNM group presented significantly higher APTw (3.7 ± 1.1% vs. 2.4 ± 1.0%, p < 0.001), MK (1.065 ± 0.185 vs. 0.909 ± 0.189, p = 0.005) and lower MD (0.989 ± 0.195 × 10-3 mm2/s vs. 1.193 ± 0.337 ×10-3 mm2/s, p = 0.035) than the non-LNM group. APTw was an independent predictor (OR = 3.115, p = 0.039) for evaluating the lymph node status through multivariate analysis. The area under the curve (AUC) of APTw (0.807) was higher than those of MK (AUC, 0.715) and MD (AUC, 0.675) for discriminating LNM from non-LNM, but the differences were not significant (all p > 0.05). Moreover, the combination of APTw, MK, and MD yielded the highest AUC (0.864), with the corresponding sensitivity of 76.5% and specificity of 88.6%. APTw and ZOOMit DKI parameters may serve as potential noninvasive biomarkers in predicting LNM of CC.