Diffusion-weighted Magnetic Resonance Imaging Scans Research Articles

Quantification of Collateral Supply with Local-AIF Dynamic Susceptibility Contrast MRI Predicts Infarct Growth.

In ischemic stroke, leptomeningeal collaterals can provide delayed and dispersed compensatory blood flow to tissue-at-risk despite an occlusion and can impact treatment response and infarct growth. The purpose of this work is to test the hypothesis that inclusion of this delayed and dispersed flow with an appropriately calculated Local Arterial Input Function (Local-AIF) is needed to quantify the degree of collateral blood supply in tissue distal to an occlusion. Seven experiments were conducted in a pre-clinical middle cerebral artery occlusion model. Dynamic susceptibility contrast MRI was imaged and post-processed to yield quantitative cerebral blood flow (qCBF) maps with both a traditionally chosen single arterial input function applied globally to the whole brain (i.e. "Global-AIF") and a delay and dispersion corrected AIF (i.e. "Local-AIF") that is sensitive to retrograde flow. Leptomeningeal collateral arterial recruitment was quantified with a pial collateral score from x-ray angiograms, and infarct growth calculated from serially acquired diffusion weighted MRI scans. The degree of collateralization at x-ray correlated more strongly with qCBF using the Local-AIF in the ischemic penumbra (R2=0.81) than traditionally chosen Global-AIF (R2=0.05). qCBF using a Local-AIF was negatively correlated (less infarct progression as perfusion increased) with infarct growth (R2 = 0.79) more strongly than a Global-AIF (R2=0.02). In acute stroke, qCBF calculated with a Local-AIF is more accurate for assessing tissue status and collateral supply than traditionally chosen Global-AIFs. These findings support use of a Local-AIF that corrects for delayed and dispersed retrograde flow in determining quantitative tissue perfusion with collateral supply in occlusive disease. MRI = magnetic resonance imaging; DSC = dynamic susceptibility contrast; PCS = pial collateral score; MCAO = middle cerebral artery occlusion; MCA = middle cerebral artery; AIF = arterial input function; rCBF = relative cerebral blood flow; qCBF = quantitative cerebral blood flow.

Dysfunction of thalamocortical circuits in early-onset schizophrenia.

Previous studies have demonstrated that the thalamus is involved in multiple functional circuits in participants with schizophrenia. However, less is known about the thalamocortical circuit in the rare subtype of early-onset schizophrenia. A total of 110 participants with early-onset schizophrenia (47 antipsychotic-naive patients) and 70 matched healthy controls were recruited and underwent resting-state functional and diffusion-weighted magnetic resonance imaging scans. A data-driven parcellation method that combined the high spatial resolution of diffusion magnetic resonance imaging and the high sensitivity of functional magnetic resonance imaging was used to divide the thalamus. Next, the functional connectivity between each thalamic subdivision and the cortex/cerebellum was investigated. Compared to healthy controls, individuals with early-onset schizophrenia exhibited hypoconnectivity between subdivisions of the thalamus and the frontoparietal network, visual network, ventral attention network, somatomotor network and cerebellum, and hyperconnectivity between subdivisions of thalamus and the parahippocampal and temporal gyrus, which were included in limbic network. The functional connectivity between the right posterior cingulate cortex and 1 subdivision of the thalamus (region of interest 1) was positively correlated with the general psychopathology scale score. This study showed that the specific thalamocortical dysconnection in individuals with early-onset schizophrenia involves the prefrontal, auditory and visual cortices, and cerebellum. This study identified thalamocortical connectivity as a potential biomarker and treatment target for early-onset schizophrenia.

Study to estimate the NIHS score and volume of stroke in predicting 30-day mortality in acute ischemic stroke patients

Background. Stroke is defined as a sudden onset of a neurological deficit attributed to a focal vascular cause. It is one of the leading causes of mortality and morbidity all over the world. The present study aimed to estimate the NIHS score and volume of stroke in predicting 30-day mortality in acute ischemic stroke patients. Material and methods. The present study was a prospective cross-sectional study conducted in 100 patients above 18 years old, of either gender, with symptoms of stroke for less than 24 hours, diagnosis of acute ischemic stroke based on history, physical examination, CT scan and/or diffusion weighted MRI scan performed during the first 24 hours. Results. In the present study, the mean age was 57.4±13.36 years. The volume of stroke on 1st day was 40.75±38.51, and on 30th day it was reduced to 31.94±33.20 which was statistically significant. NIHSS (National Institutes of Health Stroke Scale) score on day 1 was 9.70±5.22, and on day 30 it was 7.77±5.25, with a statistically significant difference (p=0.000). At the end of the 30 days, 10% mortality was observed. NIHSS score and volume of stroke were significantly associated with the 30-day outcome. Conclusion. In conclusion, integrating NIHSS scoring and stroke volume assessment into routine clinical practice enhances predictive accuracy for 30-day mortality in acute ischemic stroke patients. These findings advocate for early intervention strategies aimed at reducing stroke volume and improving neurological outcomes. Further research is recommended to validate these findings across diverse populations and settings, potentially refining acute stroke management protocol.

Diffusion MRI Metrics Characterize Postoperative Clinical Outcomes After Surgery for Cervical Spondylotic Myelopathy.

Advanced diffusion-weighted MRI (DWI) modeling, such as diffusion tensor imaging (DTI) and diffusion basis spectrum imaging (DBSI), may help guide rehabilitation strategies after surgical decompression for cervical spondylotic myelopathy (CSM). Currently, however, postoperative DWI is difficult to interpret, owing to signal distortions from spinal instrumentation. Therefore, we examined the relationship between postoperative DTI/DBSI-extracted from the rostral C3 spinal level-and clinical outcome measures at 2-year follow-up after decompressive surgery for CSM. Fifty patients with CSM underwent complete clinical and DWI evaluation-followed by DTI/DBSI analysis-at baseline and 2-year follow-up. Clinical outcomes included the modified Japanese Orthopedic Association score and comprehensive patient-reported outcomes. DTI metrics included apparent diffusion coefficient, fractional anisotropy, axial diffusivity, and radial diffusivity. DBSI metrics evaluated white matter tracts through fractional anisotropy, fiber fraction, axial diffusivity, and radial diffusivity as well as extra-axonal pathology through restricted and nonrestricted fraction. Cross-sectional Spearman's correlations were used to compare postoperative DTI/DBSI metrics with clinical outcomes. Twenty-seven patients with CSM, including 15, 7, and 5 with mild, moderate, and severe disease, respectively, possessed complete baseline and postoperative DWI scans. At 2-year follow-up, there were 10 significant correlations among postoperative DBSI metrics and postoperative clinical outcomes compared with 3 among postoperative DTI metrics. Of the 13 significant correlations, 7 involved the neck disability index (NDI). The strongest relationships were between DBSI axial diffusivity and NDI (r = 0.60, P < .001), DBSI fiber fraction and NDI (rs = -0.58, P < .001), and DBSI restricted fraction and NDI (rs = 0.56, P < .001). The weakest correlation was between DTI apparent diffusion coefficient and NDI (r = 0.35, P = .02). Quantitative measures of spinal cord microstructure after surgery correlate with postoperative neurofunctional status, quality of life, and pain/disability at 2 years after decompressive surgery for CSM. In particular, DBSI metrics may serve as meaningful biomarkers for postoperative disease severity for patients with CSM.

Usefulness of Diffusion-Weighted Imaging in Evaluating Acute Cellular Rejection and Monitoring Treatment Response in Liver Transplant Recipients.

Acute cellular rejection (ACR) is a significant immune issue among recipients following liver transplantation. Although diffusion-weighted magnetic resonance imaging (DWI) is widely used for diagnosing liver disease, it has not yet been utilized for monitoring ACR in patients after liver transplantation. Therefore, the aim of this study was to evaluate the efficacy of DWI in monitoring treatment response among recipients with ACR. This study enrolled 25 recipients with highly suspected ACR rejection, and all subjects underwent both biochemistry and DWI scans before and after treatment. A pathological biopsy was performed 4 to 24 h after the first MRI examination to confirm ACR and degree of rejection. All patients were followed up and underwent a repeated MRI scan when their liver function returned to the normal range. After data acquisition, the DWI data were post-processed to obtain the apparent diffusion coefficient (ADC) map on a voxel-by-voxel basis. Five regions of interest were identified on the liver parenchyma to measure the mean ADC values from each patient. Finally, the mean ADC values and biochemical markers were statistically compared between ACR and non-ACR groups. A receiver operating characteristic (ROC) curve was constructed to evaluate the performance of the ADC and biochemical data in detecting ACR, and correlation analysis was used to understand the relationship between the ADC values, biochemical markers, and the degree of rejection. The histopathologic results revealed that 20 recipients had ACR, including 10 mild, 9 moderate, and 1 severe rejection. The results demonstrated that the ACR patients had significantly lower hepatic ADC values than those in patients without ACR. After treatment, the hepatic ADC values in ACR patients significantly increased to levels similar to those in non-ACR patients with treatment. The ROC analysis showed that the sensitivity and specificity for detecting ACR were 80% and 95%, respectively. Furthermore, the correlation analysis revealed that the mean ADC value and alanine aminotransferase level had strong and moderate negative correlation with the degree of rejection, respectively (r = -0.72 and -0.47). The ADC values were useful for detecting hepatic ACR and monitoring treatment response after immunosuppressive therapy.

A Study to Estimate the Red Cell Width Distribution and the Mean Platelet Volume in Predicting the 30-Day Mortality in Acute Ischemic Stroke Patients.

Background Acute ischemic stroke, a clinical disorder caused by nontraumatic cerebrovascular disease, has an acute onset,frequently causesneurological deficit, and may persist for >24 hours or can be fatal in <24 hours. This studyaimed to assess the red cell width distribution (RDW) and the mean platelet volume (MPV) in predicting 30-day mortality in acute ischemic stroke patients. In general, patients with acute ischemic stroke have a rather high mortality rate in the first 30 days due to various complications, but post the 30-day mark, the prognosis is comparatively better. Material and methods The present study was conducted on patients with a confirmed diagnosis of acute ischemic stroke based on history, physical examination, CT scan, and/or diffusion-weighted MRI scan performed during the first 24 hours. It was a prospective and cross-sectional study done at Saveetha Medical College over a period of two years. The data was collected by using the intra-hospital network and was analyzed using the IBM SPSS Statistics for Windows, Version 20 (Released 2011; IBM Corp., Armonk, New York, United States). Results In the present study, among 100 patients, the mean agewas57.4 ± 13.36 years. About 55% of our subjects were males in our study. The RDW on the 1stday was 14.17 ± 0.708, and it reduced drastically on the 30thday to1st 13.55 ± 1.11, and it was statically significant (p = 0.000). The MPVon day 1 was 11.11 ± 0.969 and, on day 30, was 10.82 ± 0.90; the MPV was reduced considerably on day 30, which was statistically significant (p = 0.000). RDW on the 1stday was significantly correlated with the MPV and the volume ofstroke. Thecorrelation wassignificant at the 0.01 level (two-tailed). On the 30thday of acute ischemic stroke patients, the red blood cell (RBC)width was significantly correlated with the MPV. The correlation was significant at the 0.01 level (two-tailed). At the end of 30 days, 10% mortality was observed in the present study. Day 30 saw a significant decrease in the MPV and RDW, particularly in the moderate to severe and severe categories. The National Institutes of Health Stroke Scale (NIHSS) score and the volume of stroke were significantly associated with the 30-dayoutcome. Conclusion The RDW and the MPV are well correlated in predicting the 30-day mortality in acute ischemic stroke patients. This could potentially be used as a significant marker for predicting mortality in stroke patients in the future, but to increase the generalization, further studies need to be carried out at other demographically distinct medical centers.

374 Feasibility of Postoperative Diffusion Weighted Imaging to Assess Neural Recovery in Cervical Spondylotic Myelopathy

INTRODUCTION: Following decompressive surgery for cervical spondylotic myelopathy (CSM), advanced diffusion-weighted MRI, such as diffusion basis spectrum imaging (DBSI), may hold significant value by quantifying and tracking spinal cord microstructure. However, there is a paucity of studies investigating this topic, likely due to challenges in resolving signal distortions from spinal instrumentation. METHODS: A single-center prospective study enrolled 50 CSM patients and 20 control patients. All patients underwent preoperative and repeat diffusion-weighted MRI at two-year follow-up. All CSM patients underwent decompressive cervical surgery. DBSI metrics were extracted from the C3 spinal cord level only to minimize image artifact and reduce partial volume effects. DBSI anisotropic tensors evaluated white matter tracts through fractional anisotropy, axial diffusivity, radial diffusivity, and fiber fraction. DBSI isotropic tensors assessed extra-axonal pathology through restricted and non-restricted fraction. RESULTS: Of 50 CSM patients, 27 patients underwent both baseline and postoperative diffusion-weighted MRI scans with sufficient quality for analysis. This included 15 mild, 7 moderate, and 5 severe CSM patients, who were followed up to 23.2 (5.6, range 11.1-32.8) months. All preoperative C3 DBSI measures were significantly different between CSM and control patients (p &lt; 0.001), except DBSI fractional anisotropy (p = 0.31). At two-year follow-up, the same significance pattern was found, except DBSI radial diffusivity lost statistical significance (p = 0.75). When assessing change in C3 DBSI measures, CSM patients exhibited significant decreases in DBSI radial diffusivity (p = 0.02). Among control patients, there was no significant difference in DBSI metrics between timepoints. CONCLUSIONS: DBSI may have potential in the postoperative setting to inform clinicians of white matter tract recovery after decompressive cervical surgery for CSM.

Correlation of clinical and radiological scores for evaluation of activity in patients having thyroid-associated orbitopathy: A prospective observational study.

To find a correlation between the clinical (vision-inflammation-strabismus-appearance [VISA] score) and radiological (apparent diffusion coefficient [ADC] values) scores for evaluating disease activity in patients with thyroid-associated orbitopathy. A prospective comparative study. Our study was performed for consecutively diagnosed thyroid-associated orbitopathy (TAO) patients. Clinical evaluation included the VISA classification system with the basic thyroid workup. An inflammatory score of <4/8 was considered inactive and ≥4/8 as an active disease. Every included patient underwent a diffusion-weighted magnetic resonance imaging (DW-MRI) scan of the orbits. The orbital parameters evaluated on imaging included the proptosis, thickness, as well as the ADC values of extraocular muscles. We studied 33 consecutive patients (23 females, 69.7%) with a mean age of 41.8 years. The majority (n = 27, 81.8%) were hyperthyroid, four were hypothyroid, and two were euthyroid. In the VISA classification, nine patients had active TAO (≥4/8 inflammation score), while 24 had inactive disease. There was a positive correlation between the inflammation score and ADC values of medial rectus (MR), inferior rectus (IR) and lateral rectus (LR). We had nine patients with inflammation scores ≥4. With receiver operating characteristic (ROC) curve analysis, we found that the ADC value of IR can predict disease activity with 68% sensitivity and MR-ADC can predict active TAO with 87% sensitivity. The ADC parameters of DW-MRI are objective and less operator dependent than the clinical TAO activity scores like VISA classification. A randomized control trial may provide robust data on this correlation.

Exploring global and local processes underlying alterations in resting-state functional connectivity and dynamics in schizophrenia.

We examined changes in large-scale functional connectivity and temporal dynamics and their underlying mechanisms in schizophrenia (ScZ) through measurements of resting-state functional magnetic resonance imaging (rs-fMRI) data and computational modelling. The rs-fMRI measurements from patients with chronic ScZ (n=38) and matched healthy controls (n=43), were obtained through the public schizConnect repository. Computational models were constructed based on diffusion-weighted MRI scans and fit to the experimental rs-fMRI data. We found decreased large-scale functional connectivity across sensory and association areas and for all functional subnetworks for the ScZ group. Additionally global synchrony was reduced in patients while metastability was unaltered. Perturbations of the computational model revealed that decreased global coupling and increased background noise levels both explained the experimentally found deficits better than local changes to the GABAergic or glutamatergic system. The current study suggests that large-scale alterations in ScZ are more likely the result of global rather than local network changes.

Robust fiber orientation distribution function estimation using deep constrained spherical deconvolution for diffusion-weighted magnetic resonance imaging.

Diffusion-weighted magnetic resonance imaging (DW-MRI) is a critical imaging method for capturing and modeling tissue microarchitecture at a millimeter scale. A common practice to model the measured DW-MRI signal is via fiber orientation distribution function (fODF). This function is the essential first step for the downstream tractography and connectivity analyses. With recent advantages in data sharing, large-scale multisite DW-MRI datasets are being made available for multisite studies. However, measurement variabilities (e.g., inter- and intrasite variability, hardware performance, and sequence design) are inevitable during the acquisition of DW-MRI. Most existing model-based methods [e.g., constrained spherical deconvolution (CSD)] and learning-based methods (e.g., deep learning) do not explicitly consider such variabilities in fODF modeling, which consequently leads to inferior performance on multisite and/or longitudinal diffusion studies. In this paper, we propose a data-driven deep CSD method to explicitly constrain the scan-rescan variabilities for a more reproducible and robust estimation of brain microstructure from repeated DW-MRI scans. Specifically, the proposed method introduces a three-dimensional volumetric scanner-invariant regularization scheme during the fODF estimation. We study the Human Connectome Project (HCP) young adults test-retest group as well as the MASiVar dataset (with inter- and intrasite scan/rescan data). The Baltimore Longitudinal Study of Aging dataset is employed for external validation. From the experimental results, the proposed data-driven framework outperforms the existing benchmarks in repeated fODF estimation. By introducing the contrastive loss with scan/rescan data, the proposed method achieved a higher consistency while maintaining higher angular correlation coefficients with the CSD modeling. The proposed method is assessing the downstream connectivity analysis and shows increased performance in distinguishing subjects with different biomarkers. We propose a deep CSD method to explicitly reduce the scan-rescan variabilities, so as to model a more reproducible and robust brain microstructure from repeated DW-MRI scans. The plug-and-play design of the proposed approach is potentially applicable to a wider range of data harmonization problems in neuroimaging.

Microstructural alterations in the locus coeruleus-entorhinal cortex pathway in Alzheimer's disease and frontotemporal dementia.

We investigated invivo the microstructural integrity of the pathway connecting the locus coeruleus to the transentorhinal cortex (LC-TEC) in patients with Alzheimer's disease (AD) and frontotemporal dementia (FTD). Diffusion-weighted MRI scans were collected for 21 AD, 20 behavioral variants of FTD (bvFTD), and 20 controls. Fractional anisotropy (FA), mean, axial, and radial diffusivities (MD, AxD, RD) were computed in the LC-TEC pathway using a normative atlas. Atrophy was assessed using cortical thickness and correlated with microstructural measures. We found (i) higher RD in AD than controls; (ii) higher MD, RD, and AxD, and lower FA in bvFTD than controls and AD; and (iii) a negative association between LC-TEC MD, RD, and AxD, and entorhinal cortex (EC) thickness in bvFTD (all p<0.050). LC-TEC microstructural alterations are more pronounced in bvFTD than AD, possibly reflecting neurodegeneration secondary to EC atrophy. Microstructural integrity of LC-TEC pathway is understudied in AD and bvFTD.LC-TEC microstructural alterations are present in both AD and bvFTD.Greater LC-TEC microstructural alterations in bvFTD than AD.LC-TEC microstructural alterations in bvFTD are associated to EC neurodegeneration.

Scaling behaviours of deep learning and linear algorithms for the prediction of stroke severity.

Deep learning has allowed for remarkable progress in many medical scenarios. Deep learning prediction models often require 105-107 examples. It is currently unknown whether deep learning can also enhance predictions of symptoms post-stroke in real-world samples of stroke patients that are often several magnitudes smaller. Such stroke outcome predictions however could be particularly instrumental in guiding acute clinical and rehabilitation care decisions. We here compared the capacities of classically used linear and novel deep learning algorithms in their prediction of stroke severity. Our analyses relied on a total of 1430 patients assembled from the MRI-Genetics Interface Exploration collaboration and a Massachusetts General Hospital-based study. The outcome of interest was National Institutes of Health Stroke Scale-based stroke severity in the acute phase after ischaemic stroke onset, which we predict by means of MRI-derived lesion location. We automatically derived lesion segmentations from diffusion-weighted clinical MRI scans, performed spatial normalization and included a principal component analysis step, retaining 95% of the variance of the original data. We then repeatedly separated a train, validation and test set to investigate the effects of sample size; we subsampled the train set to 100, 300 and 900 and trained the algorithms to predict the stroke severity score for each sample size with regularized linear regression and an eight-layered neural network. We selected hyperparameters on the validation set. We evaluated model performance based on the explained variance (R2) in the test set. While linear regression performed significantly better for a sample size of 100 patients, deep learning started to significantly outperform linear regression when trained on 900 patients. Average prediction performance improved by ∼20% when increasing the sample size 9× [maximum for 100 patients: 0.279 ± 0.005 (R2, 95% confidence interval), 900 patients: 0.337 ± 0.006]. In summary, for sample sizes of 900 patients, deep learning showed a higher prediction performance than typically employed linear methods. These findings suggest the existence of non-linear relationships between lesion location and stroke severity that can be utilized for an improved prediction performance for larger sample sizes.

Abstract 296: Comparison of Prognostic Performance Using Quantitative Analysis of Head Computed Tomography and Apparent Diffusion Coefficient Imaging Before Target Temperature Management in Out-of-Hospital Cardiac Arrest Survivors

Aim: We compared head computed tomography (HCT) and diffusion-weighted magnetic resonance imaging (DW-MRI) findings before target temperature management (TTM) to predict neurological outcomes in out-of-hospital cardiac arrest survivors. Methods: Using prospectively collected data from a TTM registry, we included patients who underwent HCT and DW-MRI within 6 h of return of spontaneous circulation (ROSC). We examined the gray-to-white matter ratio (GWR) on HCT and apparent diffusion coefficient (ADC) values obtained through voxel-based analysis of DW-MRI. We analyzed the mean ADC value and the % voxels of ADC thresholds (percentage of voxels below ADC thresholds per total voxel) at 50-step intervals ranging from 200 to 1200 х 10 -6 mm/s, identifying thresholds that differentiate between good and poor neurological outcomes. Additionally, we analyzed the combination of pupillary light reflex (PLR) and neuron-specific enolase (NSE) values acquired at the same time points to predict the neurological outcomes. The primary outcome measure was the dichotomized cerebral performance category (CPC) at six months, defined as good (CPC 1-2) or poor (CPC 3-5). Results: Of 131 patients (26% female), 74 (57%) had poor outcomes. The time from ROSC to HCT and DW-MRI scans was 1.7h and 3.2h, respectively. The group with a good outcome had higher GWR (1.26 vs. 1.20) and mean ADC (787.10 vs. 697.49) values, but lower values in all ranges (250-1150) of ADC values (all P&lt;0.001). Mean ADC and ADC values in the range of 350-650 demonstrated better predictive performance for poor outcomes than the GWR (P &lt; 0.05). The mean ADC value had the highest sensitivity of 51.3% (95% CI 39.4-63.1; cutoff value ≤ 739.2 х 10 –6 mm 2 /s) when the false positive rate (FPR) was 0%. Furthermore, when combined with PLR and NSE values, the prognostic performance was significantly improved compared to using Mean ADC alone (0.83 vs 0.92; P&lt;0.01). Conclusions: In this cohort study, early voxel-based quantitative ADC analysis after ROSC (i.e., before TTM) was associated with poor neurological outcomes 6 months after cardiac arrest. We found that the Mean ADC value showed the highest sensitivity when the FPR was 0% and that combining the NSE and PLR values resulted in an even better prognostic performance.

Early life stress, sleep disturbances, and depressive symptoms during adolescence: The role of the cingulum bundle

Adolescence is often characterized by sleep disturbances that can affect the development of white matter tracts implicated in affective and cognitive regulation, including the cingulate portion of the cingulum bundle (CGC) and the uncinate fasciculus (UF). These effects may be exacerbated in adolescents exposed to early life adversity (ELA). We examined the longitudinal relations between sleep problems and CGC and UF microstructure during adolescence and their relation to depressive symptoms as a function of exposure to ELA. We assessed self-reported sleep disturbances and depressive symptoms and acquired diffusion-weighted MRI scans twice: in early adolescence (9–13 years) and four years later (13–17 years) (N = 72 complete cases). Independent of ELA, higher initial levels and increases in sleep problems were related to increases in depressive symptoms. Further, increases in right CGC fractional anisotropy (FA) mediated the association between sleep problems and depressive symptoms for youth who experienced lower, but not higher, levels of ELA. In youth with higher ELA, higher initial levels of and steeper decreases in sleep problems were associated with greater decreases in right UF FA, but were unrelated to depressive symptoms. Our findings highlight the importance of sleep quality in shaping fronto-cingulate-limbic tract development and depressive symptoms during adolescence.

Quantitative diffusion-weighted MRI response assessment in rhabdomyosarcoma: an international retrospective study on behalf of the European paediatric Soft tissue sarcoma Study Group Imaging Committee

ObjectiveTo investigate the feasibility of diffusion-weighted magnetic resonance imaging (DW-MRI) as a predictive imaging marker after neoadjuvant chemotherapy in patients with rhabdomyosarcoma.Material and methodsWe performed a multicenter retrospective study including pediatric, adolescent and young adult patients with rhabdomyosarcoma, Intergroup Rhabdomyosarcoma Study group III/IV, treated according to the European paediatric Soft tissue sarcoma Study Group (EpSSG) RMS2005 or MTS2008 studies. DW-MRI was performed according to institutional protocols. We performed two-dimensional single-slice tumor delineation. Areas of necrosis or hemorrhage were delineated to be excluded in the primary analysis. Mean, median and 5th and 95th apparent diffusion coefficient (ADC) were extracted.ResultsOf 134 included patients, 82 had measurable tumor at diagnosis and response and DW-MRI scans of adequate quality and were included in the analysis. Technical heterogeneity in scan acquisition protocols and scanners was observed. Mean ADC at diagnosis was 1.1 (95% confidence interval [CI]: 1.1–1.2) (all ADC expressed in * 10−3 mm2/s), versus 1.6 (1.5–1.6) at response assessment. The 5th percentile ADC was 0.8 (0.7–0.9) at diagnosis and 1.1 (1.0–1.2) at response. Absolute change in mean ADC after neoadjuvant chemotherapy was 0.4 (0.3–0.5). Exploratory analyses for association between ADC and clinical parameters showed a significant difference in mean ADC at diagnosis for alveolar versus embryonal histology. Landmark analysis at nine weeks after the date of diagnosis showed no significant association (hazard ratio 1.3 [0.6–3.2]) between the mean ADC change and event-free survival.ConclusionA significant change in the 5th percentile and the mean ADC after chemotherapy was observed. Strong heterogeneity was identified in DW-MRI acquisition protocols between centers and in individual patients.Graphical

Extramural Venous Invasion and Tumor Deposit at Diffusion-weighted MRI in Patients after Neoadjuvant Treatment for Rectal Cancer.

Background Diffusion-weighted (DW) imaging is useful in detecting tumor in the primary tumor bed in locally advanced rectal cancer (LARC) after neoadjuvant therapy, but its value in detecting extramural venous invasion (EMVI) and tumor deposit is not well validated. Purpose To evaluate diagnostic accuracy and association with patient prognosis of viable EMVI and tumor deposit on DW images in patients with LARC after neoadjuvant therapy using whole-mount pathology specimens. Materials and Methods This retrospective study included patients who underwent neoadjuvant therapy and surgery from 2018 to 2021. Innovative five-point Likert scale was used by two radiologists to independently evaluate the likelihood of viable EMVI and tumor deposit on restaging DW MRI scans in four axial quadrants (12 to 3 o'clock, 3 to 6 o'clock, 6 to 9 o'clock, and 9 to 12 o'clock). Diagnostic accuracy was assessed at both the per-quadrant and per-patient level, with whole-mount pathology as the reference standard. Weighted κ values for interreader agreement and Cox regression models for disease-free survival and overall survival analyses were used. Results A total of 117 patients (mean age, 56 years ± 12 [SD]; 70 male, 47 female) were included. Pathologically proven viable EMVI and tumor deposit was detected in 29 of 117 patients (25%) and in 44 of 468 quadrants (9.4%). Per-quadrant analyses showed an area under the receiver operating characteristics curve of 0.75 (95% CI: 0.68, 0.83), with sensitivity and specificity of 55% and 96%, respectively. Good interreader agreement was observed between the radiologists (κ = 0.62). Per-patient analysis showed sensitivity and specificity of 62% and 93%, respectively. The presence of EMVI and tumor deposit on restaging DW MRI scans was associated with worse disease-free survival (hazard ratio [HR], 5.6; 95% CI: 2.4, 13.3) and overall survival (HR, 8.9; 95% CI: 1.6, 48.5). Conclusion DW imaging using the five-point Likert scale showed high specificity and moderate sensitivity in the detection of viable extramural venous invasion and tumor deposits in LARC after neoadjuvant therapy, and its presence on restaging DW MRI scans is associated with worse prognosis. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Méndez and Ayuso in this issue.

Diffusion basis spectrum imaging detects pathological alterations in substantia nigra and white matter tracts with early-stage Parkinson's disease.

Using diffusion basis spectrum imaging (DBSI) to examine the microstructural changes in the substantia nigra (SN) and global white matter (WM) tracts of patients with early-stage PD. Thirty-seven age- and sex-matched patients with early-stage PD and 22 healthy controls (HCs) were enrolled in this study. All participants underwent clinical assessments and diffusion-weighted MRI scans, analyzed by diffusion tensor imaging (DTI) and DBSI to assess the pathologies of PD in SN and global WM tracts. The lower DTI fraction anisotropy (FA) was seen in SN of PD patients (PD: 0.316 ± 0.034 vs HCs: 0.331 ± 0.019, p = 0.015). The putative cells marker-DBSI-restricted fraction (PD: 0.132 ± 0.051 vs HCs: 0.105 ± 0.039, p = 0.031) and the edema/extracellular space marker-DBSI non-restricted-fraction (PD: 0.150 ± 0.052 vs HCs: 0.122 ± 0.052, p = 0.020) were both significantly higher and the density of axons/dendrites marker-DBSI fiber-fraction (PD: 0.718 ± 0.073 vs HCs: 0.773 ± 0.071, p = 0.003) was significantly lower in SN of PD patients. DBSI-restricted fraction in SN was negatively correlated with HAMA scores (r = - 0.501, p = 0.005), whereas DTI-FA was not correlated with any clinical scales. In WM tracts, only higher DTI axial diffusivity (AD) among DTI metrics was found in multiple WM regions in PD, while lower DBSI fiber-fraction and higher DBSI non-restricted-fraction were detected in multiple WM regions. DBSI non-restricted-fraction in both left fornix (cres)/stria terminalis (r = -0.472, p = 0.004) and right posterior thalamic radiation (r = - 0.467, p = 0.005) was negatively correlated with MMSE scores. DBSI could potentially detect and quantify the extent of inflammatory cell infiltration, fiber/dendrite loss, and edema in both SN and WM tracts in patients with early-stage PD, a finding remains to be further investigated through more extensive longitudinal DBSI analysis. Our study shows that DBSI indexes can potentially detect early-stage PD's pathological changes, with a notable ability to distinguish between inflammation and edema. This implies that DBSI has the potential to be an imaging biomarker for early PD diagnosis. • Diffusion basis spectrum imaging detected higher restricted-fraction in Parkinson's disease, potentially reflecting inflammatory cell infiltration. • Diffusion basis spectrum imaging detected higher non-restricted-fraction and lower fiber-fraction in Parkinson's disease, indicating the presence of edema and/or dopaminergic neuronal/dendritic loss. • Diffusion basis spectrum imaging metrics correlated with non-motor symptoms, suggesting its potential diagnostic role to detect early-stage PD dysfunctions.

Diffusion magnetic resonance imaging for kidney cyst volume quantification and non-cystic tissue characterisation in ADPKD.

Beyond total kidney and cyst volume (TCV), non-cystic tissue plays an important role in autosomal dominant polycystic kidney disease (ADPKD) progression. This study aims at presenting and preliminarily validating a diffusion MRI (DWI)-based TCV quantification method and providing evidence of DWI potential in characterising non-cystic tissue microstructure. T2-weighted MRI and DWI scans (b = 0, 15, 50, 100, 200, 350, 500, 700, 1000; 3 directions) were acquired from 35 ADPKD patients with CKD stage 1 to 3a and 15 healthy volunteers on a 1.5T scanner. ADPKD classification was performed using the Mayo model. DWI scans were processed by mono- and segmented bi-exponential models. TCV was quantified on T2-weighted MRI by the reference semi-automatic method and automatically computed by thresholding the pure diffusivity (D) histogram. The agreement between reference and DWI-based TCV values and the differences in DWI-based parameters between healthy and ADPKD tissue components were assessed. There was strong correlation between DWI-based and reference TCV (rho = 0.994, p < 0.001). Non-cystic ADPKD tissue had significantly higher D, and lower pseudo-diffusion and flowing fraction than healthy tissue (p < 0.001). Moreover, apparent diffusion coefficient and D values significantly differed by Mayo imaging class, both in the whole kidney (Wilcoxon p = 0.007 and p = 0.004) and non-cystic tissue (p = 0.024 and p = 0.007). DWI shows potential in ADPKD to quantify TCV and characterise non-cystic kidney tissue microstructure, indicating the presence of microcysts and peritubular interstitial fibrosis. DWI could complement existing biomarkers for non-invasively staging, monitoring, and predicting ADPKD progression and evaluating the impact of novel therapies, possibly targeting damaged non-cystic tissue besides cyst expansion. This study shows diffusion-weighted MRI (DWI) potential to quantify total cyst volume and characterise non-cystic kidney tissue microstructure in ADPKD. DWI could complement existing biomarkers for non-invasively staging, monitoring, and predicting ADPKD progression and evaluating the impact of novel therapies, possibly targeting damaged non-cystic tissue besides cyst expansion. • Diffusion magnetic resonance imaging shows potential to quantify total cyst volume in ADPKD. • Diffusion magnetic resonance imaging might allow to non-invasively characterise non-cystic kidney tissue microstructure. • Diffusion magnetic resonance imaging-based biomarkers significantly differ by Mayo imaging class, suggesting their possible prognostic value.

Evaluation of the Diagnostic Performance of F18-Fluorodeoxyglucose-Positron Emission Tomography, Dynamic Susceptibility Contrast Perfusion, and Apparent Diffusion Coefficient in Differentiation between Recurrence of a High-grade Glioma and Radiation Necrosis.

Differentiation between recurrence of brain tumor and radiation necrosis remains a challenge in current neuro-oncology practice despite recent advances in both radiological and nuclear medicine techniques. The purpose of this study was to compare the diagnostic performance of dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI), apparent diffusion coefficient (ADC) derived from diffusion-weighted imaging, and F18-fluorodeoxyglucose-positron emission tomography (F18-FDG-PET) in the differentiation between the recurrence of a high-grade glioma and radiation necrosis. Patients with a diagnosis of high-grade glioma (WHO Grades III and IV) who had undergone surgical resection of the tumor followed by radiotherapy with or without chemotherapy were included in the study. DSC perfusion, diffusion-weighted MRI, and PET scan were acquired on a hybrid PET/MRI scanner. For each lesion, early and delayed tumor-to-brain ratio (TBR), early and delayed maximum standardized uptake value (SUVmax), normalized ADC ratio, and normalized relative cerebral blood volume (rCBV) ratio were calculated and the pattern of lesional enhancement was noted. The diagnosis was finalized with either histopathological examination or the characteristics on follow-up imaging. The statistical analysis using the receiver operator characteristic curves was done to determine the diagnostic performance of DSC perfusion, 18-F FDG-PET, and ADC in differentiation between tumor recurrence and radiation necrosis. Fifty patients were included in the final analysis, 32 of them being men (64%). A cutoff value of early TBR >0.8 (sensitivity of 100% and specificity of 80%), delayed TBR >0.93 (sensitivity of 92.3% and specificity of 80%), early SUVmax >10.2 (sensitivity of 76.9% and specificity of 80%), delayed SUVmax >13.2 (sensitivity of 61.54% and specificity of 100%), normalized rCBV ratio >1.21 (sensitivity of 100% and specificity of 60%), normalized ADC ratio >1.66 (sensitivity of 38.5% and specificity of 80%), and Grade 3 enhancement (sensitivity of 100% and specificity of 60%) were found to differentiate recurrence from radiation necrosis. Early TBR had the highest accuracy (94.44%), while ADC ratio had the lowest accuracy (50%). A combination of early TBR (cutoff value of 0.8), late TBR (cutoff value of 0.93), and rCBV ratio (cutoff value of 1.21) showed a sensitivity of 100%, specificity of 92.3%, positive predictive value of 88.9%, negative predictive value of 93.7%, and an accuracy of 96.6% in discrimination between radiation necrosis and recurrence of tumor. F18-FDG-PET and DSC perfusion can reliably differentiate tumor recurrence from radiation necrosis, with early TBR showing the highest accuracy. ADC demonstrates a low sensitivity, specificity, and accuracy in differentiating radiation necrosis from recurrence. A combination of early TBR, delayed TBR, and rCBV may be more useful in discrimination between radiation necrosis and recurrence of glioma, with this combination showing a better diagnostic performance than individual parameters or any other combination of parameters.

New Diffusion Abnormalities Following Endovascular Treatment for Intracranial Atherosclerosis.

Background There are limited data on new ischemic brain lesions after endovascular treatment for symptomatic intracranial atherosclerotic stenosis (ICAS). Purpose To investigate the (a) characteristics of new ischemic brain lesions at diffusion-weighted MRI (new diffusion abnormalities) after endovascular treatment, (b) characteristics between those treated with balloon angioplasty and stent placement procedures, and (c) predictors of new ischemic brain lesions. Materials and Methods Patients with symptomatic ICAS in whom maximum medical therapy failed were prospectively enrolled between April 2020 and July 2021 from a national stroke center and underwent endovascular treatment. All study participants underwent thin-section diffusion-weighted MRI (voxel size, 1.4 × 1.4 × 2 mm3 with no section gap) before and after treatment. The characteristics of new ischemic brain lesions were recorded. Multivariable logistic regression analysis was performed to determine potential predictors of new ischemic brain lesions. Results A total of 119 study participants (mean age, 59 years ± 11 [SD]; 81 men; 70 treated with balloon angioplasty and 49 with stent placement) were enrolled. Of the 119 participants, 77 (65%) had new ischemic brain lesions. Five of the 119 participants (4%) had symptomatic ischemic stroke. New ischemic brain lesions were located in (61%, 72 of 119) and/or beyond (35%, 41 of 119) the territory of the treated artery. Of the 77 participants with new ischemic brain lesions, 58 (75%) had lesions located in peripheral brain areas. There was no evidence of a difference in the frequency of new ischemic brain lesions between the balloon angioplasty and stent groups (60% vs 71%, P = .20). In adjusted models, cigarette smoking (odds ratio [OR], 3.6; 95% CI: 1.3, 9.7) and more than one operative attempt (OR, 2.9; 95% CI: 1.2, 7.0) were independent predictors of new ischemic brain lesions. Conclusion New ischemic brain lesions on diffusion-weighted MRI scans were common after endovascular treatment for symptomatic intracranial atherosclerotic stenosis, and occurrence may be associated with cigarette smoking and the number of operative attempts. Clinical trial registration no. ChiCTR2100052925 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Russell in this issue.